Search

Consider a product take-back regulation with remanufacturing target imposed on a manufacturer. The manufacturer is responsible for regulation compliance by remanufacturing the product collected from multiple geographic regions. The channel alternatives for the manufacturer are 1) regional third-party collection firms, 2) regional third-party collection-remanufacturing firms, 3) a third-party firm for remanufacturing, 4) in-house collection, and 5) in-house remanufacturing. The paper proposes a mixed-integer linear programming problem (MILP) formulation for the manufacturer to select a combination of these channels to maximise the profit over a finite planning horizon. The decision model has the number of used products, remanufacturing approach, heterogeneity in the quality of returned products, and the remanufacturing target as constraints. We conduct numerical analysis using field study data for 200 litres of mild-steel drums in India to draw managerial insights. The vital suggestions and insights are as follows. 1) Regulators to impose incremental targets considering the current optimum level of remanufacturing. 2) A comprehensive remanufacturing target covering multi-region/market to discourage manufacturers from evading behaviour. 3) Managers to assist regional firms in increasing the recovery rate of products that can collect and remanufacture. 5) Manufacturers to remanufacture products during the decline stage of product life cycle (PLC) for higher profits. [ABSTRACT FROM AUTHOR]

Purpose: The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses. Design/methodology/approach: The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis. Findings: Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs. Research limitations/implications: The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each. Originality/value: The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses. [ABSTRACT FROM AUTHOR]

The procurement of food grains from farmers and their transportation to regional level has become decisive due to increasing food demand and post-harvest losses in developing countries. To overcome these challenges, this paper attempts to develop a robust data-driven supply chain model for the efficient procurement of food grains in India. Following the data collected from three leading wheat producing Indian regions, a mixed-integer linear programming model is formulated for minimising total supply chain network costs and determining number and location of procurement centres. The NK Hybrid Genetic Algorithm (NKHGA) is employed to cluster the villages, along with a novel density-based approach to optimise the supply chain network. Sensitivity analysis indicates that policymakers should focus on creating an adequate number of procurement centres in each surplus state, well before the start of the harvesting season. The study is expected to benefit food grain supply chain stakeholders such as farmers, procurement agencies, logistics providers and government bodies in making an informed decision. [ABSTRACT FROM AUTHOR]

Recently, ecotourism has been identified as an adaptation strategy for mitigating climate change impacts, as it can optimize carbon sequestration, biodiversity recovery, and livelihood benefits and generate new opportunities for the sustenance of the economy, environment, and society of the area endowed with natural resources and cultural values. With the growing responsibility at the global level, ecotourism resource management (ERM) becomes inevitable for its sustainable requirements. The integration of ecological and socio-economic factors is vital for ERM, as has been demonstrated by developing an Ecotourism Sustainability Maximization Model for an area under study, that is the Yuksam-Dzongri corridor (also known as Kangchendzonga Base Camp Trek), in the Khangchendzonga Biosphere Reserve (KBR), Sikkim, India. This model is based on the earlier developed ecotourism sustainability assessment (ESA) framework by the authors, which is based on the hierarchical relationship among ecotourism principles, criteria, indicators, and verifiers. Employing such relationships, this paper attempts to maximize ecotourism sustainability (ES) as a function of its sustainability principles, criteria, indicators, and verifiers, subject to the constraints identified through the safe minimum standard (SMS) approach by employing linear programming. Using 58 indicators as decision variables and 114 constraints, the model resulted in a maximum level of achievable ES with a score of 84.6%, allowing the resultant optimum values of the indicators to be maintained at the operational level. A central tenet of the model is the collective responsibility and adoption of a holistic approach involving the government, tourists, tourism enterprises, and local people. [ABSTRACT FROM AUTHOR]

This paper outlines the importance of multiple time step optimization (MTO) in river basin allocation. The principal novelty of the work presented here is to provide a methodology for how to use MTO solutions in river basin planning and real-time operation. Two approaches for using the MTO results were tested on Damodar River basin in India and are presented in the paper. Using the proposed approach, the model managed flood flows without exceeding the downstream full bank channel capacity in 35 years of available historical data, while at the same time increasing generated hydropower on average by 63% annually, and supplying an additional 350 million m3 to irrigation and industry compared to the historical levels. The results presented in this study were obtained using the new Web-based Basin Management (WEB.BM) water management model, the only water allocation model with full Linear Programming (LP) optimization capabilities available online free of charge. [ABSTRACT FROM AUTHOR]

In this paper, an application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired thermal power-generating company is presented. Results show that there is immense potential not only for significant cost savings but also for reduced logistics between different coal source-power plant pairs. The target plant load factor at each power plant can be achieved without the need of any imported coal which would not only save precious foreign exchange, but also reduce the logistics involved in the import of coal and transport to power plants. Sensitivity analyses have also been performed with varying coal supply and coal quality levels. The issue of greenhouse gas (GHG) emissions from coal-fired power plants has also been addressed. The trade-off between the optimal total cost and GHG emission targets has been explored. Results show that it is possible to significantly reduce carbon footprints with a marginal increase in the optimal total cost and without the need of import of coal. However, if it is desired to further reduce GHG emission targets, optimal total costs rise substantially with imported coal gradually substituting domestic coal. It is believed that the results presented in this paper would provide a fresh perspective with regard to the allocation and movement of coal. Finally, recommendations and concluding remarks are presented. [ABSTRACT FROM AUTHOR]

National Textile Policy 2000 and interventions in the Indian textile sector around the turn of this century were designed to introduce efficiency-enhancing policy reforms through gradual withdrawal of restrictions on the organized and of protection for the unorganized segments of the industry. Such changes are expected to have affected the relative performance of the organized and unorganized segments of the Indian garment industry by influencing their conducts differentially. Removal of capacity restrictions was expected to initiate optimal restructuring of production. Unorganized firms generally enjoying scope economies and advantage of small batches production are supposed to deal with its problem of market access through complementary linkage with larger units. In this context, the present paper seeks to compare the change in efficiency profile of the concerned segments of selected Indian states between 2001 and 2011. Output-oriented data envelopment analysis indicated that majority of both organized and unorganized firms in most of the states were technically inefficient even at the end of the study period. Use of sub-optimal inputmix turned out to be the important cause of inefficiency in the organized segment while operating on a less than optimal scalepossibly due to typically limited access to market - contributed to the inefficiency for greater part of unorganized garment units. A meta-frontier analysis indicated that the scale-enhancing policy measures possibly favoured the organized sector more than its unorganized counterpart in all the states under consideration. This draws our attention to the need for recognizing the different requirements of these two segments of firms and for adopting a segment-specific support strategy. [ABSTRACT FROM AUTHOR]

Purpose: Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency. Design/methodology/approach: DEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction. Findings: The proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels. Originality/value: The use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop and optimize a mathematical model based on a framework that integrates key concepts related to a circular economy (CE) and sharing economy (SE) for a leading manufacturer of laptops in India. Design/methodology/approach: This study mathematically modelled the integration of sharing networks in a circular production system. This is done through an optimization package that deploys a multi-objective mixed-integer linear programming model. Findings: This study evaluated the economic benefit and the environmental impact associated with the aforementioned integration in a production system. This study illustrated the inverse relationship between economic benefit and environmental impact and provided a set of solutions that can be used according to the case organizations goals, capacities and logistical capabilities. Research limitations/implications: This study will aid similarly structured companies in adopting this approach to integrate sustainable practices in their production system. It also enumerated Industry 4.0 (I4.0) use-cases that can be used to effectively implement this mathematical model. Further research can be conducted using multiple companies in an inter-dependent network to maximize synergy. Practical implications: This study will help to better understand the role of sharing networks in the circular economy model especially in the consumer electronics industry. Originality/value: This study is the first of its kind to mathematically model the integration of aspects related to SE and CE. It also validates the aforementioned model using a numerical case-study and offers decision-support to key executives within the case organization. [ABSTRACT FROM AUTHOR]

The humanitarian aid delivery problem associated with the early recovery phase of a disaster often incorporates multiple attributes. In this paper, the relative importance of various humanitarian aid attributes was measured using a discrete choice multi-attribute value method. This approach identifies all possible non-dominated pairs explicitly ranked by experts and provides an overall complete ranking of attributes. The performance score of each aid delivery plan was then calculated using the attributes' ranking by solving a corresponding linear programming model. As an application study, the issues pertaining to the early recovery phase of 2017 flood in Assam, India, were analyzed. It was concluded that the 'delivery amount' is the most preferred attribute selected by humanitarian experts. [ABSTRACT FROM AUTHOR]

Homestead farming has been the backbone agricultural economy of Kerala but the productivity of the homesteads in Kerala has yet to reach an acceptable level. In this paper the possibility of increasing the contribution of this sector through proper crop planning is sought. The optimum model was developed by using linear programming (LP) technique. The constraints included in the analysis were total area, intercropped area, investment amount and population of each enterprise. The optimum model reveal the scope of 22.83 per cent enhancement in net return as compared to net return from the existing plan. Sensitivity analysis of the optimum model revealed that further enhancement of net return in The agro-ecological region could be achieved by increasing the cropping intensity in the underutilized intercropped area and changing the binding enterprises. [ABSTRACT FROM AUTHOR]

This paper extends the conventional cost efficiency (CE) and revenue efficiency (RE) models to fully fuzzy environments to account for real situations where input-output data and their corresponding prices are not known precisely. Owing to the importance of the presence of undesirable outputs in the production process, these are also incorporated into the production technologies of the proposed models. This paper endeavours to propose fully fuzzy CE (FFCE) and fully fuzzy RE (FFRE) models where input-output data and prices include uncertainty of fuzzy forms, in particular, of triangular membership forms. Further, the concepts of fully fuzzy linear programming problems (FFLPPs) and linear ranking functions are used to transform FFCE and FFRE models into the crisp linear programming problems (LPPs), and to evaluate fuzzy CE (FCE) and fuzzy RE (FRE) measures of the decision-making units as triangular fuzzy numbers. Moreover, the proposed models are compared with some existing approaches and are also illustrated with an application to the banking sector in India for proving their acceptability and effectiveness in real-world systems. [ABSTRACT FROM AUTHOR]

This paper presents the Multi Objective Fuzzy Linear Programming (MOFLP) model, which deals with the fuzziness in resources and decision variables, closer to the real world situation. The MOFLP model is developed and applied to the Jayakwadi Project Stage-I built across the river Godavari in the State of Maharashtra, India. It focuses on the four objectives namely maximization of Net Benefits, maximization of Crop Production, maximization of Employment Generation and maximization of Manure Utilization. The level of satisfaction λ = 0.625 is worked out for compromised solution for four conflicting objectives under fuzzy environment. The MOFLP model compromised solution for irrigation planning provides Net Benefits 1522.75 (Million Rupees), Crop Production 322504.40 (Tons), Employment Generation 29.27 (Million Man Days) and Manure Utilization 147229.40 (Tons) respectively and irrigation intensity 68.50 %. The results obtained are promising for sustainable development in irrigation sector and closer to the true picture of the real world problem as it incorporates the fuzziness in both resources and decision variables simultaneously. [ABSTRACT FROM AUTHOR]

Maintenance management of a large road network with limited resources is a challenging task in developing countries like India. Road agencies expect that the condition of their road infrastructure should always above the desired level of performance even under restricted resources. This requires an integrated decision support system considering all aspects of maintenance. In this paper, a framework for optimal maintenance decisions by multi-objective approach is formulated for a road network by considering functional condition of the pavement quantified in terms of roughness and structural condition quantified in terms of rebound deflection. A multiobjective optimization model is developed using Integer Linear Programming (ILP). A novel approach to track the age of pavement is applied in the formulation of the mathematical model. The ε-constraint method is adopted to generate non-dominated solutions. Budget bound optimizing model is formulated and implemented for a typical road network of four roads and optimal maintenance scheduling is arrived. [ABSTRACT FROM AUTHOR]

In this paper, the operation of a complex system of multireservoirs with multiple objectives is being demonstrated. The multireservoir system includes uncertainties of inflows, demands to the large extent. Fuzzy set theory has been proved as a robust theory where these kinds of uncertainties have major role. In this study, the fuzzy linear programming method is used to get the better policy for the system operation with the uncertainty in various parameters i.e. resources, technological coefficients, objective function coefficients. A four reservoir system (a compound parallel and series) is taken as a case study and the fuzzification of all parameters is tried on the system. The effect of fluctuations in irrigation demand and release, power demand and release and available storage volume are considered. The consequences on the objectives i.e. maximization of returns from irrigation release, maximization of returns from power releases are also examined. The operation policies thus evolved give a better understanding of the problem and the intricate complexities associated and there effects. With this the policy makers (a decision maker) can have a wide range of options at his disposal for suitable action. [ABSTRACT FROM AUTHOR]

One of the methods for increasing productivity of water consumed in agriculture is by improved water supply management. This paper presents results from an optimization study of the Malampuzha irrigation project of the Bharathapuzha river basin of Kerala in India. The objective of this study is to determine whether significant improvements might be realized from optimization of operation of the reservoir system. To do this a mixed integer linear programming (MILP) model is developed and five different management strategies are tested. The result indicates that a management strategy with deficit irrigation by supplying less water in non-critical growth period and maximum water during stress sensitive periods is a best viable solution for better performance. A MILP model, rather than a linear programming (LP) model, is used to ensure that the reservoir does not spill before reaching its capacity. [ABSTRACT FROM AUTHOR]

The present paper demonstrates the applicability of population based search optimization method, namely, Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project (MBSP), India. Ten different strategies of DE are employed to assess the ability of DE for solving higher dimensional problems as an alternative methodology for irrigation planning. The parameters considered in DE are population size, crossover constant and weighting factor. Linear Programming (LP) is utilized as a comparative approach to assess the ability of DE. Comparison of results of LP and the 10 DE strategies for the given parameters indicated that both the results are comparable even for high dimensional problems. Extensive sensitivity analysis studies, performed for 3,600 combinations of above parameters for the 10 DE strategies suggested that DE/rand-to-best/1/bin strategy is the best strategy giving maximum benefits taking minimum CPU time. It is concluded that DE can be utilized for efficient planning of any irrigation system with suitable modifications. [ABSTRACT FROM AUTHOR]

This paper presents an Interactive Fuzzy Multi-Objective Linear Programming (IFMOLP) model for water quality management in a river basin. The IFMOLP model formulated will first evaluate dissolved oxygen (DO) concentrations or DO deficits at a point in different reaches depending on the overall Biochemical Oxygen Demand (BOD) concentration present in the respective drain. Subsequently, the model incorporates the aspirations and conflicting objectives of the decision maker (DM) by taking into consideration the aspects relevant for pollution control boards as well as dischargers responsible for generating wastewater. The uncertainty associated with specifying the water quality criteria (based on DO concentration or DO deficit) and treatment cost to remove pollution level is incorporated by interacting the decision maker. In this process DM is asked to specify the reference aspiration levels of achievement for the values of all membership functions generated with respect to each objective. This provides flexibility for the pollution control authorities and dischargers to specify their aspirations. IFMOLP model developed herein is then used in a case study for the evaluation of optimal BOD removal in different drains located across the river Yamuna at New Delhi, India. The presented model will simulate the allocation of waste load efficiencies with satisfactory results which will indicate usefulness of the model in managing more complex river basins along with better flexible policies of water management. [ABSTRACT FROM AUTHOR]

This paper presents a linear programming model for optimal water allocations in a large river basin system. The model is applied to the transboundary Subernarekha River in India, which has two main stream reservoirs, two barrages, and three small command area reservoirs. The Tripartite Agreement (TPA) among the cobasin riparian states for sharing of its waters is analyzed. The main objective is to find the maximum annual benefits from irrigation and hydropower subject to various constraints on the system. Design constraints as per the TPA relating to the water shares among riparian states (i.e., Bihar, Orissa, and West Bengal) at individual dams and barrages are also considered. Optimal water allocations are obtained based on the 75% water year dependable flow as specified in the TPA. Water shortage and water surplus years have also been considered to determine optical water allocations during the dry and wet years, respectively. The stream reservoirs Chandil and Icha would fail to meet the water demands during the low flow years, whereas the Kharkai and Galudih barrages would essentially satisfy water demands according to the TPA provisions. Results indicate that Bihar is likely to benefit most from the TPA. [ABSTRACT FROM AUTHOR]

In this research, we utilise a multi-method braided approach for a real-world health care intervention in rural India. We first use action research to conceptually underpin the role of self-help groups, disease profiles and appropriate interventions in health care behaviour change and improvement. Action research is then coupled with a non-linear integer-programming-based simulation to determine how health care resources need to be distributed over time, disease type and groups. The action research provides specific research questions and distributional forms needed for the optimisation analysis, while the non-linear integer-programming simulation provides specific recommendations on where and when to distribute resources. External validity of the study is ensured by the adoption of recommendations in the field as part of the action research. Findings from this research have important policy implications. For example, it identifies the value of continuous embedded interventions as opposed to periodic ones and the importance of flexibility in terms of which community groups and disease types to serve over time. This research also provides an important bridge between the operations research, health care in developing nations, organisational theory and humanitarian operations bodies of knowledge. [ABSTRACT FROM AUTHOR]

Industrialization has caused dire consumption of resources and has already caused acute damage to the environment. Due to stringent environmental regulations, organizations are enforced to adopt sustainability strategies such as reuse, repair, reduce, and remanufacturing. To remanufacture products, manufacturing organizations have to transform their supply chains to be closed or circular. In this study, a mathematical model is formulated to transform a traditional linear supply chain into a closed-loop supply chain (CLSC) for an organization located in India. It is accomplished by incorporating remanufacturing with reverse logistics into the supply chain to achieve sustainability thereby satisfying the sustainable development goals (SDGs). A multi-objective mixed-integer linear programming approach was used to formulate the model to optimize the supply chain to improve the operations of manufacturing, recycling, repair, and disposal to minimize the environmental effects and to maximize the net profit of the product. The GAMS optimization software was used to solve the model, and sensitivity analysis was carried out to validate the robustness of the proposed network. The result states that the organization can make profits by adopting the SDGs. Industry can optimize the number of parts to be repaired, dismantled, recycled, and determine the supplier's optimum quantity of parts purchase. Lack of awareness on the potential of sustainable CLSCs is hindering its acceptance in the economy. The proper use of the proposed model not only helps the organization to maximize profit but also minimizes the environmental impact by attaining sustainability. This study is helpful for organizations that are eco-conscious and are willing to balance economic profit and environmental well-being by adopting sustainability in CLSCs. [ABSTRACT FROM AUTHOR]

A well-developed and efficient banking sector is the fundamental requirement for the smooth functioning of any economy. The present study is an attempt to examine the technical, pure technical and scale efficiencies of the Indian banks across different ownership categories for the period 2010-12. Seven out of the selected 44 banks lie on the efficiency frontier and form the reference set for their peers. Further, it is observed that efficiency scores do not vary much across public sector, private sector and foreign banks. The performance of public sector and private sector banks is almost at par with respect to technical efficiency, whereas in the case of foreign banks, there is scope for improving scale efficiency. [ABSTRACT FROM AUTHOR]

Indian power systems are designed to operate at a nominal frequency of 50 Hz. They face hourly demands that exceed their generation capacity during certain hours of a day and operate at a lower frequency in those hours. In general, each state (province) has an electric utility with a generation capacity that comprises: (i) state (provincial) government owned generation plants, (ii) independent power producers (IPPs) and (iii) assigned portion of outputs of central (federal) government owned generation plants. The state government and central government plants and IPPs offer to sell energy to a State's utility through offer bids. A State's utility may draw additional power from a central generator in excess of its assigned portion of output and it is termed as an un-scheduled interchange (UI). The utility will pay for this UI to the central generator using an hourly tariff rate known as availability-based tariff (ABT). ABT is a function of the operating frequency. This study captures this operational model, ABT structure and proposes a mixed integer linear-programming formulation to optimally commit and schedule units in the utility for 24 h. The proposed model and results on actual data are reported. The system includes a pumped-hydro unit. [ABSTRACT FROM AUTHOR]

Abstract: Routing of floods is essential to control the flood flow at the flood control station such that it is within the specified safe limit. In this paper, the applicability of the extended Muskingum method is examined for routing of floods for a case study of Hirakud reservoir, Mahanadi river basin, India. The inflows to the flood control station are of two types – one controllable which comprises of reservoir releases for power and spill and the other is uncontrollable which comprises of inflow from lower tributaries and intermediate catchment between the reservoir and the flood control station. Muskingum model is improved to incorporate multiple sources of inflows and single outflow to route the flood in the reach. Instead of time lag and prismoidal flow parameters, suitable coefficients for various types of inflows were derived using Linear Programming. Presently, the decisions about operation of gates of Hirakud dam are being taken once in 12 h during floods. However, four time intervals of 24, 18, 12 and 6 h are examined to test the sensitivity of the routing time interval on the computed flood flow at the flood control station. It is observed that mean relative error decreases with decrease in routing interval both for calibration and testing phase. It is concluded that the extended Muskingum method can be explored for similar reservoir configurations such as Hirakud reservoir with suitable modifications. [Copyright &y& Elsevier]

Purpose - The purpose of this research is to provide exploratory insights on measurement of efficiency of the hotel and restaurant companies operating in India. Design/methodology/approach - This study will use a linear programming-based approach, data envelopment analysis (DEA), to evaluate the efficiency of hotel and restaurant companies operating in India. DEA is a method of evaluating the relative efficiency of decision-making units (DMUs). In this study the decision-making units are the hotel and restaurant companies. The study further explores if there exists a relationship between the efficiency and size of the hotel and restaurant companies. Findings - The DEA model used in this study assigns efficiency scores to each of the hotel and restaurant companies taken in the sample of 68 companies for the year 2004-2005. The study also explores whether there is a relationship between the efficiency and size of the hotel and restaurant companies. Practical implications - As this study evaluates the efficiency of the hotel and restaurant sector, it separates the most efficient hotel and restaurant companies from the non-efficient ones. The study identifies the top performers in this sector. Also, managers get important insights for their strategic and operational decisions to improve performance. Originality/value - There are very few known studies that have measured the efficiency of the hotel and restaurant companies. This study is one of the few exploratory initiatives in the Indian context. [ABSTRACT FROM AUTHOR]

Mumbai, the largest metropolitan city in India, generated 6,256 tons of waste per day in 2001. It is the responsibility of the Municipal Corporation of Greater Mumbai (MCGM) to provide Municipal Solid Waste (MSW) management services; however, the MCGM is not able to handle the increasing quantity of waste. As a result, waste litters all over the place giving rise to health and environmental problems. Hence, there is a need to involve private sector and community participation in waste management. In this paper, a linear programming model is developed to integrate different options and stakeholders involved in MSW management in Mumbai. Various economic and environmental costs associated with MSW management are taken into consideration while developing the model. [ABSTRACT FROM AUTHOR]

Zero-one linear programming is a well-accepted approach for decision making for many real world problems. Optimal selection of collieries from a set of collieries for reconstruction is a policy of the concerned authority. The selected collieries are funded for reconstruction based on certain criteria. No colliery will be partially funded, as it is not possible to reconstruct the colliery partially so it is required either to select or reject a colliery for reconstruction. Further, in the real field generally the data available are imprecise in nature. The present paper is concerned with the application of fuzzy 0-1 linear programming to select optimally a set of collieries from a given set of colliery projects for reconstruction with an optimal planning under existing constraints and fuzzy goals. The reconstruction problem is posed as multi objective decision making problem. The application potentiality of the model has been examined by using it in the context of a group of collieries need reconstruction investments in the Jharia Coalfield, Jharkhand, INDIA. [ABSTRACT FROM AUTHOR]

Many developing countries have emphasis on distributed generation (DG) technology for their generation expansion planning. The planning considerations and judicious choice of attributes are dictated by prevailing conditions. The attributes considered are capital costs, energy not served per annum, and profits from injecting power into the grid at peak load, all of which are important for a developing country. The uncertain futures considered are three possible loading conditions, which can be low, medium and high. Different scenarios (plans) are generated by various combinations of configurations. DGs can be configured as stand-alone mode, hybrid operation, or micro-grid formation with or without grid connection. With the increased complexities in DG planning options along with the multiple attributes to be accounted, more sophisticated techniques other than conventional economic analysis are needed to arrive at correct decisions by decision makers. The analytical hierarchy process (AHP) is used for obtaining relative weights in an objective way. Further, the statistical method like interval-based multi-attribute decision making with tradeoff analysis is used for shortlisting the feasible plans and identifying the most appropriate plan. It is proposed to use the weights obtained from AHP for finding the performance efficiencies in data envelopment analysis (DEA) for evaluating the plans. A new composite utility function is proposed to resolve cases where performance efficiency is insufficient for evaluation in DEA application. The sample system is derived with reference to a rural electrification scheme in India. The assessment of plans is presented and discussed. The comparative strengths and weaknesses of the methods are reported on the basis of the results obtained. [ABSTRACT FROM AUTHOR]

Purpose: This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical. Design/methodology/approach: Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model. Findings: As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team. Research limitations/implications: Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection. Originality/value: The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to assess the university libraries in North East India regarding their initiatives towards open access movement and conceptualize a model for Open Access Initiatives (OAI). Approach, Design and Methodology: Surveyed and identified all the universities in the eight states of North East India. Covered 11 central, 5 state and 4 private universities to understand open access initiatives taken up by them in their respective libraries collecting data through a semi-structurally designed questionnaire. Using statistical techniques, data have been analyzed to draw empirical conclusions. Findings: The study have revealed various issues associated with the libraries regarding their automation status, digitization process, different motives towards OA, establishment of institutional repositories, challenges and many more. The need for having a model for OAI for all the libraries of the region has been felt. Came out with a proposed model for OAI having eight phases comprising mainly of rejuvenation of library system, digitization, digital archiving, OA publications, constitution of a committee, etc. However, acceptability of the model by the libraries of the region needs to be taken care of by the concerned universities. Originality/value: The study is first of its kind in the area of open access initiatives taken up in the region. Findings provide a new vista for the university libraries, which are added feature in the context of the stock of the existing knowledge in the field. The conceptualized OAI model is a new proposal the acceptability of which being rest with the universities concerned. [ABSTRACT FROM AUTHOR]

Supplier selection is a critical process in sustainable supply chain management. Increased pressure from stakeholders has forced companies to search for methodologies that help in arriving at intelligent supplier selection decisions. This is a unique study as it illustrates how to optimise orders among various suppliers while taking into consideration all three dimensions of sustainability – economic, social, and environmental. Previous studies have mostly relied on simple ranking of suppliers on the basis of past performance for selection. Those studies that did emphasise on optimisation of orders among suppliers, did not consider all three dimensions of sustainability. To establish an improved sustainable supply chain, this study uses integrated fuzzy AHP and fuzzy multi-objective linear programming approach for order allocation among suppliers. fuzzy AHP has been used for weighing various factors such as quality, lead time, cost, energy use, waste minimisation, emission, and social contribution, and weights of the factors have been considered for developing linear programming. Demand has been taken as a fuzzy variable in this model. The case of an Indian automobile company has been taken as illustration. [ABSTRACT FROM PUBLISHER]

The problem of irrigation planning becomes more complex by considering an uncertainty. The uncertainties can be tackled by formulating the problem of irrigation planning as Fuzzy Linear Programming (FLP). FLP models can incorporate the scenario of real world problem. In the present study, Multi Objective Fuzzy Linear Programming (MOFLP) irrigation planning model is formulated for deriving the optimal cropping pattern plan for the case study of Jayakwadi project in the Godavari river sub basin in Maharashtra State, India. Four conflicting objectives are considered such as Net Benefits (NB), Crop/Yield Production (CP), Employment Generation/Labour Requirement (EG) and Manure Utilization (MU). Four different cases are considered to incorporate the uncertainty in MOFLP model. To include the uncertainty in irrigation planning problem only objectives are taken as fuzzy and constraints are crisp in nature in Case-I. To consider the uncertainty involved in availability of resources, in Case-II the stipulations are fuzzy. The technological coefficients are fuzzy in Case-III. The Case-IV includes both technological coefficients and stipulations fuzzy. The level of satisfaction ( λ) works out to be 0.58, 0.50, 0.50 and 0.28 respectively for Case-I to IV. The results obtained in Case-IV are more realistic and promising as it involves the uncertainty in technological coefficients and stipulations simultaneously. [ABSTRACT FROM AUTHOR]

A weekly irrigation planning LP model is formulated for determining the optimal cropping pattern and reservoir water allocation for an existing storage based irrigation system in India. Objective of the model is maximization of net annual benefit from the project. In an irrigation planning of a storage based irrigation system, initial storage of the reservoir at the beginning of the reservoir operation, expected inflows into the reservoir during each intraseasonal period, capacity of channels, crop calendar and yield response to water deficit in each growth stage of crop play a vital role in deciding acreage and water allocation to each crop. The planning model takes into account yield response to water deficit in each intraseasonal period of the crop, expected weekly inflows entering into the reservoir, storage continuity of reservoir, land and water availability, equity of water allocation among sub areas and proportionate downstream river release. One year comprising of 52 weeks is considered as planning horizon. To account for uncertainty in water resources availability, the model is solved for four levels of reliability of weekly inflows entering into the reservoir (90%, 85%, 80% and 75%). Alternative optimal cropping patterns and weekly releases to crops grown in each sub area under each main canal are obtained for various states of initial storage at the beginning of reservoir operation and for various levels of weekly inflows into the reservoir. Results reveal the importance of initial state of reservoir storage for feasible solution and shows the impact on cropping pattern with the change in initial storage of reservoir for different levels of reliability of weekly inflows. [ABSTRACT FROM AUTHOR]

Nutritional profiles of 25 feed ingredients available in India were selected and compiled. Their costs were ascertained from Cochin (SW), Tuticorin (SE), and Bhubaneswar (NW), where fish/shrimp farming is traditionally practiced. Least-cost feed formulations (using the linprog toolbox in Matlab software) were attempted for catfish, milkfish, tilapia, and grouper fry specifying levels of four critical limits: Ca/P ratio, digestible energy (DE), 10 amino acid levels (where data was available), and 10 ingredients, totaling 26 constraining limits to the model. Feeds formulated for catfish fry cost US$0.066 kg-1 at Bhubaneswar, US$0.117 kg-1 at Tuticorin, and US$0.153 kg-1 at Cochin, with poultry by-product meal and hydrolyzed feather meal as the major ingredients; limiting amino acids in these feeds were methionine and phenylalanine. Feeds formulated for milkfish fry cost US$0.110 kg-1 at Cochin, US$0.108 kg-1 at Tuticorin, and US$0.072 kg-1 at Bhubaneswar; the limiting amino acids in this case were histidine and threonine. The cost of feeds for tilapia fry was US$0.207 kg-1 at Cochin, US$0.369 kg-1 at Tuticorin, and US$ 0.114 kg-1 at Bhubaneswar; the limiting amino acid was methionine. Feed formulae for fry of Asian sea bass had an LP solution containing only five ingredients for all three places. The feed formula was the same for Cochin and Bhubaneswar market prices, and the total cost of ingredients was US$0.274 kg-1 and US$0.142 kg-1, respectively. At Tuticorin market prices, the feed formula cost was US$0.397 kg-1. The feed formulae for grouper fry at Bhubaneswar and Tuticorin market prices had the same three ingredients costing US$0.114 kg-1 and US$0.321 kg-1, respectively, whereas feed formula for Cochin market price consisted of four ingredients costing US$0.280 kg-1. [ABSTRACT FROM AUTHOR]

The article presents a study which aims to assess the extent of technical efficiency in 27 public sector banks operating in India and to give strict ranking to the banks. The study used two renown data envelop analysis (DEA) models, CCR model and Andersen and Petersen's super-efficiency model, as well as the cross-sectional data for financial year 2004/2005. to obtain technical efficiency scores. Moreover, it notes that only 27 banks are discovered to be efficient and defined the efficient boundary and technical efficiency scores ranges from 0.632 to 1.

A rubber factory in India encountered extensive amount of rework at the rubber mixing stage for one of its medicare products, the hot water bag. The scorch time and the optimum cure time of the rubber-mixing compound were the potential product parameters for which this rework took place. Regression analysis shows that the process parameters, the temperature of the dispersion kneader and the temperature of the open mill, with adjusted R2 values of 79.9 and 89.5%, respectively can predict both the scorch time and the optimum cure time. Subsequently analyzing the multiple linear regression equation for optimum cure time, which is the key process output variable, with the help of linear programming has arrived at the optimum levels of these temperatures. Besides this, analysis of variance for scorch time has shown that the mixing technique of the workers is not identical. Duncan's multiple range tests has revealed operator group 3 as the best performer for scorch time. Bartlett's test has revealed inequality of variances of four operator groups for optimum cure time. This substantiated the training need of the concerned operators. The study has resulted in reduction of the extent of rework from 80762 to 17865 PPM. Naturally this substantial reduction in rework will reduce the process cycle time and cost of production immensely. [ABSTRACT FROM AUTHOR]

ABSTRACTThis study aims to find the optimal switching point for the Indian coal-based power plants to switch to a cost-effective technology and reduce particulate emissions. Regulation in the form of an emission standard, an emissions tax, an ash tax, or a coal tax provides an incentive for the power plants to abate. We have taken a period of 40 years to show the pattern of abatement in a sample of 40 power plants. Linear programming using GAMS has been used for the analysis to determine when the plants will shift to cost-efficient technology. We have first done the analysis on a firm-to-firm basis and then we have aggregated to show the variability of our results. [ABSTRACT FROM AUTHOR]

In this article, linear programming and fuzzy optimization models are developed for planning and management of available land-water-crop system of Mahanadi-Kathajodi delta in eastern India. The models are used to optimize the economic return, production and labour utilization, and to search the related cropping patterns and intensities with specified land, water, fertilizer and labour availability, and water use pattern constraints. Due to extreme backwardness of the study area, it has been decided to keep all the three objectives of the linear programming models at the same priority level to obtain the compromised solution in a fuzzy environment that incorporates the imprecision in fuzzy goals and fuzzy constraints. These non-structural models facilitate the conjunctive use of available surface water and groundwater resources. A comparative evaluation along with the benefit-cost ratios of the existing and proposed farming systems is also presented. [ABSTRACT FROM AUTHOR]

This study to address the issues involved in the planing and design of a computer waste management system in an integrated manner. A decision-support tool is presented for selecting an optimum configuration of computer waste management facilities (segregation, storage, treatment/processing, reuse/recycle and disposal) and allocation of waste to these facilities, The model is based on an integer linear programming method with the objectives of minimizing environmental risk as well as cost. The issue of uncertainty in the estimated waste quantities from multiple sources is addressed using the Monte Carlo simulation technique. An illustrated example of computer waste management in Delhi, India is presented to demonstrate the usefulness of the proposed model and to study tradeoffs between cost and risk. The results of the example problem show that it is possible to reduce the environ- mental risk significantly by a marginal increase in the available cost. The proposed model can serve as a powerful tool to address the environmental problems associated with exponentially growing quantities of computer waste which are presently being managed using rudimentary methods of reuse, recovery and disposal by various small-scale vendors. [ABSTRACT FROM AUTHOR]

The recent global scenario in the mineral sector may be characterized by rising competitiveness, increasing production costs and a slump in market price. This has pushed the mineral sector in general and that in the developing countries in particular to a situation where the industry has a limited capacity to sustain unproductive costs. This, more often than not, results in a situation where the industry fails to ensure environmental safeguards during and after mineral extraction. The situation is conspicuous in the Indian coal mining industry where more than 73% production comes from surface operations. India has an ambitious power augmentation projection for the coming 10 years. A phenomenal increase in coal production is proposed from the power grade coalfields in India. One of the most likely fall-outs of land degradation due to mining in these areas would be significant reduction of agricultural and other important land-uses. Currently, backfilling costs are perceived as prohibitive and abandonment of land is the easy way out. This study attempts to provide mine planners with a mathematical model that distributes generated overburden at defined disposal options while ensuring maximization of backfilled land area at minimum direct and economic costs. Optimization has been accomplished by linear programming (LP) for optimum distribution of each year's generated overburden. Previous year's disposal quantity outputs are processed as one set of the inputs to the LP model for generation of current year's disposal output. From various geo-mining inputs, site constants of the LP constraints are calculated. Arrived value of economic vectors, which guide the programming statement, decides the optimal overburden distribution in defined options. The case example (with model test run) indicates that overburden distribution is significantly sensitive to coal seam gradient. The model has universal applicability to cyclic system (shovel-dumper combination) of opencast mining of stratified deposits. [ABSTRACT FROM AUTHOR]

The present investigation was an attempt to develop a Spatial Decision Support System (SDSS) for a test Nagwan watershed situated in the Damodar-Barakar catchment in India, the second most seriously eroded area in the world, for not only estimating sediment yields under prevailing resource management systems but also designing a linear programming (LP)-based optimized land-use plan for soil loss reduction in the test watershed. The proposed SDSS was validated on 9 years (1981-1983, 1985-1989, and 1991) of sediment yield data for the test watershed. This showed that the SDSS could mimic the annual dynamics of the total sediment yields at the test watershed outlet with a correlation coefficient of 0.65, model efficiency coefficient of 0.70, mean relative error of -17.97%, and root mean square prediction error of 9.63 t ha -1 . It could also be used as an efficient tool for assessing sediment yields from different parts of the test watershed and for designing a linear programming (LP)-based optimized land-use plan for reduced total sediment yields from the test watershed. The LP-based land-use plan proposed no change in the total areas under paddy, corn, and forest land-use types but suggested their re-distribution within the test watershed, thereby leading to not only a reduction in the test watershed's total sediment yield by about 14.61% but also an increase in its paddy and corn crop productivities by 2.80 and 68.14%, respectively. The proposed LP-based land-use plan for the test watershed could thus lead to an enhanced productivity benefit of about Rs 3735 ha -1 , in monetary terms, from corn crop cultivation at its optimal locations. [ABSTRACT FROM AUTHOR]

The article evaluates the efficiency of a sample of farms from West Bengal, India within a linear programming (LP) model. The parameters of the model to be used from sample data on inputs and outputs are estimated. The article focuses on the problem of estimating the non-zero elements of the matrix. Optimal solutions are compared with actual farm outputs to measure efficiency. Several statistical tests regarding mean efficiency ratings of groups of farms are performed.