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Applied Simulation and Optimization: In Logistics, by Miguel Mujica Mota, Idalia Flores De La Mota

By Miguel Mujica Mota, Idalia Flores De La Mota

Presenting innovations, case-studies and methodologies that mix using simulation techniques with optimization strategies for dealing with difficulties in production, logistics, or aeronautical difficulties, this publication offers ideas to universal commercial difficulties in different fields, which variety from production to aviation difficulties, the place the typical denominator is the mix of simulation’s flexibility with optimization strategies’ robustness.

Providing readers with a finished advisor to take on comparable concerns in business environments, this article explores novel how you can face business difficulties via hybrid methods (simulation-optimization) that enjoy the benefits of either paradigms, so as to provide options to special difficulties in provider undefined, construction techniques, or offer chains, corresponding to scheduling, routing difficulties and source allocations, between others.

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Vonolfen, M. Affenzeller, A. Beham, E. Lengauer, and S. Wagner. Simulation-based evolution of resupply and routing policies in rich vendor-managed inventory scenarios. Central European Journal of Operations Research, 21(2):379–400, March 2013. 49. S. Vonolfen, M. Affenzeller, A. Beham, S. Wagner, and E. Lengauer. Simulation-based evolution of municipal glass-waste collection strategies utilizing electric trucks. In Proceedings of the IEEE 3rd International Symposium on Logistics and Industrial Informatics (Lindi 2011), pages 177–182, August 2011.

M. Law. Simulation Modeling and Analysis. McGraw-Hill, 2007. 31. Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer, 3rd edition, 1999. 32. N. Moin and S. Salhi. Inventory routing problems: a logistical overview. Journal of the Operational Research Society, 58:1185–1194, 2007. 33. J. Momoh. Electric Power System Applications of Optimization. CRC / Taylor & Francis, 2009. 34. S. S. Panwalkar and W. Iskander. A survey of scheduling rules. Operations Research, 25(1):45– 61, Jan-Feb 1977.

For each day of operation, the accumulated demands are converted into a standard capacitated vehicle routing problem (CVRP) instance which can be solved with any VRP algorithm available in HeuristicLab. net. Simulation-Based Optimization with HeuristicLab: Practical Guidelines … VMI Customers VehicleAgent VendorAgent 23 VMICustomerAgent Replenish Tours VRPAlgorithm ReplenishmentPolicy Inventory Orders Demands CVRPInstance Inventory Information Order-based Customers OrderCustomerAgent VehicleAgent VendorAgent Tours Replenish VRPAlgorithm Inventory Orders Inventory Information OrderPolicy CVRPInstance Demands Fig.

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