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A multi-objective model for risk mitigating in supply chain design
Authors:Vahid Nooraie  Masoud Narenji  Mahour M Parast  Panagote M Pardalos  P M Stanfield
Affiliation:1. Department of Industrial and Systems Engineering, North Carolina A&2. T State University, Raleigh, NC, USA;3. Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, USA;4. Center for Applied Optimization, University of Florida, Gainesville, FL, USA
Abstract:The goal of this study is to recognise various factors for responsive SCs that affect supply risk and model their impact on SC design and operation. We propose a conceptual model for SC responsiveness that encompasses practices such as flexibility, agility, internal integration, and visibility. This conceptual model is utilised to build up a multi-objective, multi-period SC design and operation model. A heuristic algorithm is developed to find the supplier, product, period, and production rate for the numerical problem. The improved genetic algorithm (GA) produces solutions with more accuracy in considerably less time than a traditional GA. Finally, an approach to prioritise the objective functions is developed that allows managers to focus on specific objective functions more than optimum values. This approach provides risk-averse, responsiveness-oriented, cost-effective managers the capability to set priorities based on their policies.
Keywords:supply chain  responsiveness  risk  genetic algorithm
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