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Purpose: A common problem in mega cities is congestion, due to the size of the automotive park, this makes that the perishable foods decreasing their organoleptic characteristics or increases their losses, which requires considering the effect of time on routing problems. The state of the art demonstrates the need to formulate new routing models that include the specific characteristics of perishable foods in order to reduce their losses. Design/methodology/approach: A mathematical model was formulated based on two classical models: the three-index vehicle flow model proposed by (Golden, Assad, Levy & Gheysens, 1984) and the time window model proposed by (Cordeau, Desaulniers, Desrosiers, Solomon & Soumis, 1999). We proposed a novel VRP Model that permits reductions loss due to the perishable. Findings: The optimum cost is found with AMP® for twenty nodes, six vehicles and six fruits. For more nodes, a two-phase strategy is proposed, first a clustering based on a modified p-median model and then a VRP for each cluster. Research limitations/implications: The results showed the need to investigate multiobjective models, since the performance measures can be efficiency, quality and response capacity; the model can be applied in other supply chains of perishable foods. Social implications: According to FAO in Logistics practices in the last mile generate between 10-30% of the perishable food loss in developing countries' mega-cities. Originality/value: A last-mile logistics strategy is proposed to manage delivery routes for fresh fruits in mega-cities, considering the effect of congestion through travel time in the perishability function. The new model it uses the flow variable to control the amount of each fruit arriving to each node and the time variable to define fruit waste or loss depending on the time and type of fruit. [ABSTRACT FROM AUTHOR]

Introduction- In a production Line it's important that the stations' cycle times are balanced and that they are low since this allows to reduce the work in process. However, doing this leads to an increase in the stations' number, that is not favorable because it raises the costs associated with the stations, therefore it is necessary to define strategies that allow achieving a balance between these requirements. Objective- In this article we propose the formulation of a model for the line balancing, using the technique of multi-objective goal programming, applied to the pharmaceutical industry in order to minimize the stations' number, minimize cycle time and inventory in process. Methodology- Goal programming is used to address a line balance model, which considers at the same time the assignment of multiple stations to one operation and the assignment of multiple operations to one station. Results- A significant decrease in cycle time and idle time at minimum costs is achieved, and a comparison between the deterministic and stochastic models is presented. Conclusions- Through this implementation of the LINGO model, the compliance of the proposed restrictions, the precedence of operations and the proper functioning of the model were validated through the optimal solutions obtained. The simulation is a tool that illustrates the complexity of the operations of the production system, which require, as in our case, a more realistic modeling to understand the behavior of the process and evaluate different strategies. [ABSTRACT FROM AUTHOR]

Introduction: this study proposes a method to design and balance a cellular manufacturing system of a typical industrial company to obtain an optimal configuration in terms of the process, total cost, idle time and reliability criteria. Methods: the developed method has three phases. The first phase obtains candidate solutions using optimization models to minimize the cycle time and total cost. In the second phase, the performance measures for the remaining criteria of each candidate solution are found using discrete-event simulation. In the last phase, the optimal configuration is selected using the analytic network process (ANP). Results: the proposed method was validated with a practical case, where the optimal configuration had the best reliability with a zero-smoothness index, which minimized the wasted time and excess inventory. However, it was not the configuration with the lowest cost. Conclusions: This method has two contributing elements: multiple lean criteria and the approach, which combines different solution strategies to select the best configuration in an integral manner. [ABSTRACT FROM AUTHOR]

The Cutting stock problem is of great importance for manufacturing companies that involving the process of cutting large rolls of some material into small strips of different widths, considering the effect this has on product inventories in process and raw materials. Proper management of this problem not only generates beneficial economic but also generates sustainable impacts, to the extent that seeks a balance between the cost of inventory and process waste. This paper first presents an overview of what complexity means in solving a problem of this type in a company. His background is set out with the most important works in the literature, highlighting some Colombian jobs. Then, we present classification problem and suggestions from other aspects are provided to consider when addressed cutting stock problem. Finally are framed the four most common approaches to solution giving ideas for future research, hoping thereby contribute to the development of the topic. [ABSTRACT FROM AUTHOR]

This paper shows a methodology based on neural networks to prioritize some market areas with a business approach. In this research, we try to resolve the uncertainty that exists in most organizations around the priority of a market area. The research problem is supported by the lack of tools to estimate the priority of a market area and for the lack of an effective interface between logistics and marketing departments. To solve this situation we used a special neural network (Kohonen Maps). These maps are a type of neural network to facilitate the grouping of customers and they allow determining which the most are frequently affecting the previously established criteria dealing prioritization. Finally, three scenarios are propose to validate the behavior of neural networks to prioritize market areas. [ABSTRACT FROM AUTHOR]

This article presents an analytic model for managing inventories in a butchers shops, considering the costs of obsolescence and stockout. In order to handle the cost of obsolescence we consider a variety of prices which were decreased while the product remains in storage. This aim of the model is to determine the optimal order quantity to maximize the utility in the point of sale of pork. We present the analysis of obsolescence and the possibility of supplying pork meat per cut type and also considering to buy the whole pork. [ABSTRACT FROM AUTHOR]

Transfer Stations are facilities dedicated to management, and solid waste transfer of a vehicle to another with greater capacity, which transports them to their place of use or disposal. The main purpose of the research is to represent the location of these kind facilities through a model of mixed integer linear programming, which consider different characteristics of stations such as total capacity and materials recovery. Total costs minimization is the main objective. To do this, we minimize opening fixed costs, transportation costs and operating costs evaluated at the current time through a function of present cost equivalent. [ABSTRACT FROM AUTHOR]

Traditionally assembly lines have been used to produce high volumes of a single model. To take advantage of these lines in flexible manufacturing environments, we can implement mixed model lines which allow manufacturing different products of a family in the same line, however, its balancing requires different techniques that traditional. In this research, a literature review was made to analyze the factors affecting the mixed model lines in MTO environments and based on this we developed a mathematical optimization model to stabilize workloads making easier the decision about production sequences that are programmed on the line. The model was run in several instances and the results were significantly better than those obtained with a line balancing traditional method. [ABSTRACT FROM AUTHOR]

Introduction. Cutting stock problem covers the issue of cutting big rolls of any material (paper, fabrics, steel, wood, etc) in small shreds with different widths that, can, then, be used as the raw materials to elaborate a final product. The lengths of these shreds are defined by the clients or according to the specific conditions required by the production process. Objective. Developing a mathematical model that allows the planning and the programming of a cutting process for steel rolls in order to solve the question "how to configure the cutting of rolls satisfying the requirements of the demand and simultaneously minimize the remains and the inventory levels in a metallurgic company? Materials and methods. A methodological model was made and applied in a production plant in which Steel pipes are made. Waste levels of about 15% per cut roll were found in the place. Results. This, under lost weight terms, reached up to 25 tons per 1700 tons produced in a month, thus making the inventory levels of in process products to be exceeded by up to 24% of the storage capacity. Conclusions. The main result of the methodology is a 4% reduction of the weekly cost of waste, compared to the real process of the company. [ABSTRACT FROM AUTHOR]

Introduction. This research addresses the problem of internal materials supply operations in a pre-milling type concentrate food plant. The required amount of raw materials for production in the internal supply chain is determined by minimizing the total relevant operational cost, made up by the setup cost and the stock maintenance cost, which maximizes efficiency of the resources used in the process. This study takes into account such factors as capacity of the hoppers, the time-dependent setup sequence, routes of supply hoppers, filling rates and supply times, based on a model of mixed-integer linear programming. Objective: Provide a strategy that allows efficient use of resources in the production process, subjected to the demand of materials from the material requirements planning (MRP) of the company under study. Materials and methods. The short-term multi-period model defines the scheduling of elevators and conveyors for each time period, and the amount of raw materials that is sent to each hopper and bins. Results. This research determines the amount of initial stock required to operate, as well as the operations strategy that the company under study must follow, so that it meets the demand for raw materials, making efficient use of the resources used in the production process. Conclusion. In the analysis of results and presentation of scenarios, the most representative cost, the one related to stock maintenance, could be observed. Since this is a critical factor for companies belonging to this sector, we present an innovative proposal, both in practice and in the literature, to contribute to minimizing the total setup cost and the cost of maintenance of raw material stock in hoppers through a rational use of resources. [ABSTRACT FROM AUTHOR]

In this paper a methodology for planning and control of production in the medium term is proposed for the textile industry sector in a make to order environment. The methodology is based on two phases arising from the characteristics of the production system. In the first phase, an aggregate planning model, which allows the calculation of quantities produced in the own workshop and the amount to outsource of clothes to work on so that it meets the economic objectives and obtain the greatest benefit for the industry in the planning horizon. In the second stage, an operations programming model is proposed, which aims at producing sequences for the quantities that need to be produced in the workshop so that the make span is reduced. The two proposed phases constitute an important tool to support decision-making on production management in the textile sector. [ABSTRACT FROM AUTHOR]

Introduction. The problem of determining the capacity in service companies is the lack of clear methodologies. As for academic institutions, the research advances on the subject are even more reduced. The literature available has widely covered other problems affecting capacity, and also the programming and the planning of staff, facilities and schedules without directly measuring capacity. Objective. To create a generic methodology to determine the capacity of an educative services system (schools, universities, etc) in terms of the quantity of students to serve with the institution's infrastructure. Materials and methods. Firstly, a methodology to simulate the capacity used by the students throughout time is created. Then, with this information, an optimization model to calculate the maximum number of students that can be admitted is executed. Results. The model developed is applied in the Engineering School of Universidad del Valle, Colombia, where it was found that 25% more of students could have been admitted, using about 20 % of the capacity that can be potentially used. Conclusion. This methodological model is useful to know the capacity in terms of the number of students an institution can receive. It also facilitates midterm decisions, especially the measurement of the impact of the policies that can be formulated to favor the maximization of the service standards of the institution, and also, for instance, the impact of building new infrastructures. [ABSTRACT FROM AUTHOR]

This paper propose an additional plan of production in a Company, including employees in a handicap condition, which will count with different times to execute the different tasks and sometimes incompatible in specific activities. The Model of mixed integer linear programming seeks to maximize production as well as the respective cash flow. The tributary benefits of the Colombian government associated to the inclusion of handicap condition personnel, are considered for the model. The Model is validated with a case study. [ABSTRACT FROM AUTHOR]