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Solving an integrated production and transportation problem (IPTP) is a very challenging task in semiconductor manufacturing with turnkey service. A wafer fabricator needs to coordinate with outsourcing factories in the processes including circuit probing testing, integrated circuit assembly, and final testing for buyers. The jobs are clustered by their product types, and they must be processed by groups of outsourcing factories in various stages in the manufacturing process. Furthermore, the job production cost depends on various product types and different outsourcing factories. Since the IPTP involves constraints on job clusters, job-cluster dependent production cost, factory setup cost, process capabilities, and transportation cost with multiple vehicles, it is very difficult to solve when the problem size becomes large. Therefore, heuristic tools may be necessary to solve the problem. In this paper, we first formulate the IPTP as a mixed integer linear programming problem to minimize the total production and transportation cost. An efficient genetic algorithm (GA) is proposed next to tackle the problem when it becomes too complicated. The objectives are to minimize total costs, where the costs include production cost and transportation cost, under the environment with backup capacities and multiple vehicles, and to determine an appropriate production and distribution plan. The results demonstrate that the proposed GA model is an effective and accurate tool. [ABSTRACT FROM AUTHOR]

Abstract: Good inventory management is essential for a firm to be cost competitive and to acquire decent profit in the market, and how to achieve an outstanding inventory management has been a popular topic in both the academic field and in real practice for decades. As the production environment getting increasingly complex, various kinds of mathematical models have been developed, such as linear programming, nonlinear programming, mixed integer programming, geometric programming, gradient-based nonlinear programming and dynamic programming, to name a few. However, when the problem becomes NP-hard, heuristics tools may be necessary to solve the problem. In this paper, a mixed integer programming (MIP) model is constructed first to solve the lot-sizing problem with multiple suppliers, multiple periods and quantity discounts. An efficient Genetic Algorithm (GA) is proposed next to tackle the problem when it becomes too complicated. The objectives are to minimize total costs, where the costs include ordering cost, holding cost, purchase cost and transportation cost, under the requirement that no inventory shortage is allowed in the system, and to determine an appropriate inventory level for each planning period. The results demonstrate that the proposed GA model is an effective and accurate tool for determining the replenishment for a manufacturer for multi-periods. [Copyright &y& Elsevier]

Owing to today's increasingly competitive market and ever-changing manufacturing environment, the inventory problem is becoming more complicated to solve. The incorporation of heuristics methods has become a new trend to tackle the complex problem in the past decade. This article considers a lot-sizing problem, and the objective is to minimise total costs, where the costs include ordering, holding, purchase and transportation costs, under the requirement that no inventory shortage is allowed in the system. We first formulate the lot-sizing problem as a mixed integer programming (MIP) model. Next, an efficient genetic algorithm (GA) model is constructed for solving large-scale lot-sizing problems. An illustrative example with two cases in a touch panel manufacturer is used to illustrate the practicality of these models, and a sensitivity analysis is applied to understand the impact of the changes in parameters to the outcomes. The results demonstrate that both the MIP model and the GA model are effective and relatively accurate tools for determining the replenishment for touch panel manufacturing for multi-periods with quantity discount and batch transportation. The contributions of this article are to construct an MIP model to obtain an optimal solution when the problem is not too complicated itself and to present a GA model to find a near-optimal solution efficiently when the problem is complicated. [ABSTRACT FROM AUTHOR]

Abstract: Because of the pressing need for maintaining a healthy environment with reasonable costs, China is moving toward the trend for generating electricity from renewable resources. Both solar energy and wind power have received a tremendous attention from private associations, political groups, and electric power companies to generate power on a large scale. A drawback is their unpredictable nature and dependence on weather. Fortunately, the problems can be partially tackled by using the strengths of one source to overcome the weakness of the other. Especially, a large fraction of the solar resource is available at times of peak electrical load. However, the complexity of using two different resources together makes the hybrid solar-wind generation systems more difficult to analyze. Accordingly, this paper first briefly introduces the solar-wind generation system and next develops its critical success criteria. Then, a fuzzy analytic hierarchy process associated with benefits, opportunities, costs and risks, is proposed to help select a suitable solar-wind power generation project. [Copyright &y& Elsevier]

Abstract: With growing worldwide awareness of environmental protection, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer in the long term. A performance evaluation system for green suppliers thus is necessary to determine the suitability of suppliers to cooperate with the firm. While the works on the evaluation and/or selection of suppliers are abundant, those that concern environmental issues are rather limited. Therefore, in this study, a model for evaluating green suppliers is proposed. The Delphi method is applied first to differentiate the criteria for evaluating traditional suppliers and green suppliers. A hierarchy is constructed next to help evaluate the importance of the selected criteria and the performance of green suppliers. Since experts may not identify the importance of factors clearly, the results of questionnaires may be biased. To consider the vagueness of experts’ opinions, the fuzzy extended analytic hierarchy process is exploited. With the proposed model, manufacturers can have a better understanding of the capabilities that a green supplier must possess and can evaluate and select the most suitable green supplier for cooperation. [Copyright &y& Elsevier]

Abstract: In today’s highly competitive environment, a good supply chain relationship is essential for a company to survive and to acquire reasonable profit. While a few large companies may be able to vertically integrate from the design stage to the final distribution of the entire supply chain, most companies can only focus on their specialized functions and to cooperate with upstream or downstream companies. Supplier selection, as a result, is very important for maintaining strategic alliances. The objective of this paper is to develop a fuzzy multiple goal programming (FMGP) model to help downstream companies to select thin film transistor liquid crystal display (TFT-LCD) suppliers for cooperation. Fuzzy analytic hierarchy process (FAHP) is applied first to analyze the importance of multiple factors by incorporating experts’ opinion, and these factors include cost, yield and number of suppliers. Multi-choice goal programming is used next to consider the limits of various resources and to formulate the constraints. From the experimental design and examination, we can testify that the proposed model not only can consider multi-choice goals, decision-making behavior and limit of resources, it can also allocate the purchase among the selected supplier(s). [Copyright &y& Elsevier]

Abstract: This paper applies a two-phase methodology to cluster 366 records of the wire bond machines for a Taiwanese IC packaging foundry, where six attributes of each machine are chosen to cluster. The purpose of clustering in this paper is to help the foundry more effectively assign a family of machines to orders that appear in various forms such as emergent or quality-demanding and are highly dynamic in nature. Given the clusters, we use the technique of parallel coordinates to plot each attribute’s centers in clusters so that the foundry can take advantage of visualization to determine what machines can be assigned to orders. To plot these centers, we map the input values into the range of −1 and +1 so that proper parallel coordinates can be used. Originating from the graphs, we also compare the same machines appearing in clusters that are produced by applying different clustering methods. These identical machines form the important basis to support the clustering results for the management of machines. [Copyright &y& Elsevier]

Abstract: With today’s keen competition, semiconductor market has changed from producer-oriented to customer-oriented. To be successful, companies need to consider both customer satisfaction in demand and the ultimate profit goal of companies. Semiconductor fabricators today must face an environment with multi-product types and multi-priority orders. Since semiconductor fabrication has a very complicated production process, the production planning of different products types and priority levels is an even more difficult task to experts. The objective of this study is to construct an analytical approach under a fuzzy subjective judgment environment, in which fuzzy analytic hierarchy process (AHP) method with entropy weight is utilized to deal with uncertainty, to generate performance ranking of different priority mixes. The results provide guidance to experts in a fab regarding strategies for accepting orders with the consideration of manufacturing efficiency in the aspects of product, equipment efficiency and finance. [Copyright &y& Elsevier]

This paper considers the control wafers safety inventory problem (CWSIP) in the wafer fabrication photolithography area. The objective is to minimize the total cost of control wafers, where the cost includes new wafers cost, re-entrant cost and holding cost while maintaining the same level of production throughput. For the problem under pulling control production environment, a nonlinear programming model is presented to set safety inventory levels so as to minimize total cost of control wafers. A numerical example is given to illustrate the practicality of the model. The results demonstrate that the proposed model is an effective tool for determining the service level of safety inventory of control wafers for each grade. [ABSTRACT FROM AUTHOR]

Assembly lines are often indispensable in factories, and in order to attain a certain level of assembly line productivity, multiple goals must be considered at the same time. However, these multiple goals may conflict with each other, and this is a multi-objective assembly line balancing problem. This study considers four objectives, namely minimizing the cycle time, minimizing the number of workstations, minimizing the workload variance, and minimizing the workstation idle time. Since the objectives conflict with each other, for example, minimizing the cycle time may increase the number of workstations, the fuzzy multi-objective linear programming model is used to maximize the satisfaction level. When the problem becomes too complicated, it may not be solved by the fuzzy multi-objective linear programming model using a mathematical software package. Therefore, a genetic algorithm model is proposed to solve the problem efficiently. By studying practical cases of an automobile manufacturer, the results show that the proposed fuzzy multi-objective linear programming model and the genetic algorithm model can solve small-scale multi-objective assembly line balancing problems efficiently, and the genetic algorithm model can obtain good solutions for large-scale problems in a short computational time. Datasets from previous works are adopted to examine the applicability of the proposed models. The results show that both the fuzzy multi-objective linear programming model and the genetic algorithm model can solve the smaller problem cases and that the genetic algorithm model can solve larger problems. The proposed models can be applied by practitioners in managing a multi-objective assembly line balancing problem. [ABSTRACT FROM AUTHOR]

The prevalence of business-to-business (B2B) has made the relationship among firms more closer than ever. Whether in simple arm-length transactions or business cooperation, many firms, in order to reduce costs and achieve efficiency, have shifted their day-to-day operations from the tradition of relying on manpower to the use of information technology in handling tasks such as inventory, procurement, production planning, distribution, etc. As a result, the need of a business process information system is imminent for firms to coordinate with partners in the supply chain and to be sustainable in the competitive market. This study thus proposes a hybrid multi-criteria decision-making approach for evaluating business process information systems. First, the factors that should be taken into account in selecting an appropriate system are explored. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) is adopted next to understand the interrelationships among the criteria. Based on the results from the DEMATEL, the Fuzzy Analytic Network Process (FANP) is applied to calculate the importance of the factors. Fuzzy Techniques for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the business process information systems. The interrelationship among the factors should be considered in the decision-making; thus, the FANP can be a recommended methodology. However, the FANP questionnaire is usually very lengthy and cumbersome. The use of DEMATEL in advance can shorten the questionnaire substantially. FTOPSIS is used to rank the alternatives so that the pairwise comparisons of the alternatives required in the FANP can be avoided. Fuzzy set theory is incorporated in the study so that the uncertainty and ambiguity present in decision-making can be considered. The proposed approach can provide references for decision makers for making relevant decisions and can be revised and adopted in similar problems. [ABSTRACT FROM AUTHOR]

The vehicle routing problem (VRP) is a challenging combinatorial optimization problem. This research focuses on the problem under which a manufacturer needs to outsource materials from other suppliers and to ship the materials back to the company. Heterogeneous vehicles are available to ship the materials, and each vehicle has a limited loading capacity and a limited travelling distance. The purpose of this research is to study a multiple vehicle routing problem (MVRP) with soft time window and heterogeneous vehicles. Two models, using mixed integer programming (MIP) and genetic algorithm (GA), are developed to solve the problem. The MIP model is first constructed to minimize the total transportation cost, which includes the assignment cost, travelling cost, and the tardiness cost, for the manufacturer. The optimal solution can present multiple vehicle routing and the loading size of each vehicle in each period. The GA is next applied to solve the problem so that a near-optimal solution can be obtained when the problem is too difficult to be solved using the MIP. A case of a food manufacturing company is used to examine the practicality of the proposed MIP model and the GA model. The results show that the MIP model can obtain the optimal solution under a short computational time when the scale of the problem is small. When the problem becomes non-deterministic polynomial hard (NP-hard), the MIP model cannot find the optimal solution. On the other hand, the GA model can obtain a near-optimal solution within a reasonable amount of computational time. This paper is related to several important topics of the Symmetry journal in the areas of mathematics and computer science theory and methods. In the area of mathematics, the theories of linear and non-linear algebraic structures and information technology are adopted. In the area of computer science, theory and methods, and metaheuristics are applied. [ABSTRACT FROM AUTHOR]

Ocean energy is abundant in China, and the utilization of ocean energy could improve current energy structure and contribute to energy security. If tidal power is harnessed efficiently, it could help China reach its renewable energy goals. A suitable model for solving the multi-criteria decision-making problem is proposed in this paper. The model incorporates the fuzzy analytic network process (FANP) and the fuzzy goal programming (FGP). The FANP can consider various factors, the interrelationships among the factors, and the impreciseness and vagueness of the problem more thoroughly based on expert opinions. The FGP can help select dam sites to maximize the satisfaction of the system when resources are limited. A case study in an east-coast province in China is presented to demonstrate the practicality of the proposed model. [ABSTRACT FROM AUTHOR]

Because of the maturity of advanced technologies and the urgent requirement of maintaining a healthy environment with reasonable price, generating electricity from alternative resources in China will become the main trend in the near future. However, how to prioritize a suitable strategic planning of energy sources among stakeholders has not been comprehensively discussed in previous literatures and is becoming more important and complex. Accordingly, the paper employs a fuzzy analytic hierarchy process model, which incorporates the benefits, opportunities, costs and risks (BOCR) concept, to help in prioritizing energy sources. [ABSTRACT FROM AUTHOR]

Companies need to be innovative to survive in today's competitive market; thus, new product development (NPD) has become very important. This research constructs an integrated NPD framework for developing new products. In stage one, customer attributes (CAs) and engineering characteristics (ECs) for developing products are collected, and fuzzy interpretive structural modelling (FISM) is applied to understand the relationships among these critical factors. Based on quality function deployment (QFD), a house of quality is then built, and fuzzy analytic network process (FANP) is adopted to calculate the relative importance of ECs. In stage two, fuzzy failure mode and effects analysis (FFMEA) is applied to understand the potential failures of the ECs and to determine the importance of ECs with respect to risk control. In stage three, a goal programming (GP) model is constructed to consider the outcome from the FANP-QFD, FFMEA and other objectives, in order to select the most important ECs. Due to pollution and global warming, environmental protection has become an important topic. With both governments and consumers developing environmental consciousness, successful green and low-carbon NPD provides an important competitive advantage, enabling the survival or renewal of firms. The proposed framework is implemented in a panel manufacturing firm for designing a green and low-carbon product. [ABSTRACT FROM PUBLISHER]

Abstract: Due to the impacts of fossil and nuclear energy on the security, economics, and environment in the world, the demand of alternative energy resources is expanding consistently and tremendously in recent years. Wind energy production, with its safe and environmental characteristics, has become the fastest growing renewable energy source in the world. The construction of new wind farms and the installation of new wind turbines are important processes in order to provide a long-term energy production. In this research, a comprehensive evaluation model, which incorporates interpretive structural modeling (ISM) and fuzzy analytic network process (FANP), is constructed to select suitable turbines when developing a wind farm. A case study is carried out in Taiwan in evaluating the expected performance of several potential types of wind turbines, and experts in a wind farm are invited to contribute their expertise in determining the importance of the factors of the wind turbine evaluation and in rating the performance of the turbines with respect to each factor. The most suitable turbines for installation can finally be generated after the calculations. The results can be references for decision makers in selecting the most appropriate wind turbines. [Copyright &y& Elsevier]

Abstract: With natural resource scarcity and environmental protection, the use of renewable energy has become a promise for offering clean and plentiful energy. Photovoltaic (PV) solar cell is one of the emerging renewable energy applications; however, it suffers a large difficulty in high production cost with low conversion efficiency currently. Hence, an urgent pressure to upgrade technology and to formulate product strategy is evident in the solar cell power industry. In order to prosper PV silicone solar cell power industry, the paper develops a conceptual model, which is composed of a fuzzy analytic network process with interpretive structural modeling and benefits, opportunities, costs and risks, to help analyze suitable strategic products. The empirical study shows that the conceptual model can effectively and precisely handle such a complicated problem and can lead to an outstanding performance result. [ABSTRACT FROM AUTHOR]

Abstract: The move to integrating distribution management system (DMS) and feeder management system (FMS) in China is becoming the main trend in recent years, in addition to upgrading and rebuilding existing energy management system (EMS) and DMS. However, with increasing complexity in the social environments along with rapidly changing technologies, how to select a suitable contractor and a FMS project is becoming an important issue for electric power companies. This paper first briefly introduces FMS and then lists its critical success criteria. A model that applies a multi-criteria decision-making (MCDM) method, an analytic network process (ANP) associated with benefits, opportunities, costs and risks (BOCR), is constructed to help power companies to select the most suitable FMS project. [Copyright &y& Elsevier]

Abstract: With maturity of advanced technologies and urgent requirement for maintaining a healthy environment with reasonable price, China is moving toward a trend of generating electricity from renewable wind resources. How to select a suitable wind farm becomes an important focus for stakeholders. This paper first briefly introduces wind farm and then develops its critical success criteria. A new multi-criteria decision-making (MCDM) model, based on the analytic hierarchy process (AHP) associated with benefits, opportunities, costs and risks (BOCR), is proposed to help select a suitable wind farm project. Multiple factors that affect the success of wind farm operations are analyzed by taking into account experts'' opinions, and a performance ranking of the wind farms is generated. [Copyright &y& Elsevier]

Abstract: In a competitive market, semiconductor fabricator must face an environment with multi-product types, multi-priority orders and demand changes in time. Since semiconductor fabrication has a very complicated production process, the above-stated characteristics make the production planning even more difficult. This paper applies data envelopment analysis (DEA) to find a set of product family mix that is efficient for the company to produce. To ensure long-term effectiveness in productivity and in profit gaining, window analysis is adopted to seek the most recommended set of product family mixes for manufacturing by measuring the performance changes over time. With this method, the performance of a mix in one period is compared not only with the performance of other mixes but also with its own performance in other periods. The proposed mechanism can provide guidance to the fabricator regarding strategies for aggregate planning so as to improve manufacturing efficiency. [Copyright &y& Elsevier]

As the consciousness of human beings in preserving the world increases, the demand of alternative energy resources has been expanding exponentially in recent years, and wind power is one of the most promising renewable energy resources. Taiwan, with its abundant coastal wind resources and good geographical conditions, is very suitable for developing wind farms. The development and implementation of renewable energy regulations have defined a direction for future renewable energy development in Taiwan. This also shows Taiwan's determination to follow the footsteps of the developed countries and the commitment to environmental protection. Therefore, the decision making of wind farms has become the most important link for the construction of wind farms in the future. This paper proposed a fuzzy analytic network process with benefit–opportunity–cost–risk approach to systemize the complicated decision making of wind farm site selection. A case study is carried out to examine the proposed approach and to evaluate the performance of several existing wind farms in Taiwan. By adopting the systematic analysis method, the most suitable wind farm can be determined, and the results can be references for planning and development of wind power industry in the future. [ABSTRACT FROM AUTHOR]