Simulation-Optimization in Logistics, Transportation, and SCM

• Format: eBook
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: agent-based simulation; and control; assignment problem; automated parcel lockers; biased-randomized heuristics; clustering; composite priority rules; container terminal; discrete event simulation; distribution networks; dockless bike-sharing system; e-groceries; Earth Sciences, Geography, Environment, Planning; facility location Problems; fuzzy logic; genetic algorithm; Geography; guidance; heuristics; horizontal cooperation; horizontal transportation; hybrid flow shop; hybrid modeling; hyper-parameter optimization; last-mile delivery; liner network design; local search; location routing problem; logistics; machine learning; machine qualifications; maritime transportation; Markovian queueing network; matlab-simulink; meta-heuristic; Monte Carlo simulation; navigation; neighborhood search; neural networks; nonlinear-flight-mechanics; omnichannel retail stores; optimization; optimization simulation; pick-up and delivery; Reference, Information and Interdisciplinary subjects; relocation; Research and information: general; scheduling; scrap; shortest processing time; simheuristics; simulation; simulation-based optimization; stochastic project scheduling; synchronization; system dynamics; tabu search; uncertainty; unequal demand; vehicle routing problem; warehouse; weather uncertainty
• ISBN: 3036512616; 9783036512600; 9783036512617; 3036512608
• DOI: 10.3390/books978-3-0365-1261-7

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.