Simulation-Optimization in Logistics, Transportation, and SCM

Transportation, logistics, and supply chain systems and networks constitute one of the pillars of modern economies and societies. From sustainable traffic management in smart cities or air transportation to green and socially responsible logistics practices, many enterprises and governments around t...

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Other Authors: Juan, Angel A. (Editor), Rabe, Markus (Editor), Goldsman, David (Editor), Faulin, Javier (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
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DOAB: description of the publication
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700 1 |a Goldsman, David  |4 edt 
700 1 |a Faulin, Javier  |4 edt 
700 1 |a Juan, Angel A.  |4 oth 
700 1 |a Rabe, Markus  |4 oth 
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245 1 0 |a Simulation-Optimization in Logistics, Transportation, and SCM 
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520 |a Transportation, logistics, and supply chain systems and networks constitute one of the pillars of modern economies and societies. From sustainable traffic management in smart cities or air transportation to green and socially responsible logistics practices, many enterprises and governments around the world have to make decisions that affect the efficiency of these complex systems. Typically, optimization algorithms are employed to deal with these challenges, and simulation approaches are utilized when considering scenarios under uncertainty. However, better results might be achieved by hybridizing both optimization algorithms with simulation techniques to deal with real-life transportation, logistics, and SCM challenges, which often are large-scale and NP-hard problems under uncertainty conditions. Hence, simheuristic algorithms (combining metaheuristics with simulation) as well as other simulation optimization approaches constitute an effective way to support decision makers in such complex scenarios. This reprint presents a collection of selected articles on simulation optimization in transportation, logistics, and supply chain management. The reprint is strongly connected to the topics covered in the Winter Simulation Conference (WSC) track on logistics, transportation, and SCM, which includes a stream in simheuristic algorithms as well. 
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546 |a English 
650 7 |a Information technology industries  |2 bicssc 
650 7 |a Computer science  |2 bicssc 
653 |a omnichannel retail stores 
653 |a vehicle routing problem 
653 |a pick-up and delivery 
653 |a biased-randomized heuristics 
653 |a simheuristics 
653 |a scheduling 
653 |a uncertainty 
653 |a discrete event simulation 
653 |a hybrid flow shop 
653 |a scrap 
653 |a local search 
653 |a tabu search 
653 |a machine qualifications 
653 |a clustering 
653 |a shortest processing time 
653 |a maritime transportation 
653 |a liner network design 
653 |a synchronization 
653 |a weather uncertainty 
653 |a optimization simulation 
653 |a discrete-event simulation 
653 |a simulation-based optimization 
653 |a assignment problem 
653 |a neighborhood search 
653 |a warehouse 
653 |a nonlinear-flight-mechanics 
653 |a neural networks 
653 |a guidance, navigation, and control 
653 |a machine learning 
653 |a model 
653 |a matlab-simulink 
653 |a stochastic project scheduling 
653 |a genetic algorithm 
653 |a composite priority rules 
653 |a agent-based simulation 
653 |a horizontal cooperation 
653 |a e-groceries 
653 |a optimization 
653 |a simulation 
653 |a logistics 
653 |a distribution networks 
653 |a container terminal 
653 |a meta-heuristic 
653 |a horizontal transportation 
653 |a hyper-parameter optimization 
653 |a hybrid modeling 
653 |a system dynamics 
653 |a facility location Problems 
653 |a Monte Carlo simulation 
653 |a automated parcel lockers 
653 |a last-mile delivery 
653 |a location routing problem 
653 |a heuristics 
653 |a fuzzy logic 
653 |a dockless bike-sharing system 
653 |a Markovian queueing network 
653 |a relocation 
653 |a unequal demand 
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