supply chain management
Maedeh Fasihi; Seyed Esmaeil Najafi; Reza Tavakkoli-Moghaddam; Mostafa Hahiaghaei-Keshteli
Abstract
The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development ...
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The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development of aquaculture and recycling of returned goods in reverse logistics would significantly help with preserving water resources, as well as sustainable development. Therefore, government agencies and aquaculture industry beneficiaries are interested in reverse logistics. This study is focused on the optimization of a closed-loop supply chain of fish. To this end, a new bi-objective mathematical model is proposed that both minimizes total costs and maximizes fulfilling customers demand in uncertainty situation. Several well-known multi-objective meta-heuristic algorithms and a proposed hybrid meta-heuristic algorithm are applied to identify Pareto solutions. The solutions are then compared in terms of performance metrics. Also, the epsilon-constraint method and sensitivity analysis are used to validate the algorithms and evaluate the performance of the model. Lastly, the VIKOR method is used to select the superior method. To demonstrate the capability of the proposed model, a closed-loop supply chain of trout in northern Iran is investigated as a case study. The results show that the developed model could be effective in reducing the costs and increasing customer satisfaction.
Faezeh Asadian Ardakani; Ali Morovati Sharifabadi
Volume 10, Issue 26 , January 2012, , Pages 75-94
Abstract
One of the solutions for solving cutting stock problem in differentindustries, such as sheet metal, lumber, glass, paper and textile, isapplying ,Particle Swarm Optimization to minimize the waste ofrawmaterials. This article is intended to solve two-dimensional cuttingproblem. In these problems, larger ...
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One of the solutions for solving cutting stock problem in differentindustries, such as sheet metal, lumber, glass, paper and textile, isapplying ,Particle Swarm Optimization to minimize the waste ofrawmaterials. This article is intended to solve two-dimensional cuttingproblem. In these problems, larger rectangular plates, divided intosmaller rectangularsegments, aim to minimizing the number of usedplates or the waste of plates by considering demand. In this articlePSO is used. To enhance the efficiency of algorithm, and preventingoverlap in cutting problem, the CUL algorithm is used. In order toinvestigate the results of algorithm, new software has been designed.This software has two ways for solving the problem. First, it ends upwith optimized cutting pattern considering the number and dimensionof segments and, length and width of main plate. Also, there is apossibility to give different width to software, in this case, thesoftware gives the user the optimum cutting pattern and optimumlength of main plate in addition to optimum width
