1. Mathematical Modeling and Intelligent Optimization in Green Manufacturing & Logistics.
- Author
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Ren, Yaping and Ren, Yaping
- Subjects
Mathematics & science ,Research & information: general ,AGV charging ,AGV scheduling ,EOL product ,IoT ,K-means algorithm ,NSGA-II algorithm ,asynchronous parallel disassembly ,auto parts supply chain ,bi-objective model ,cloud-edge collaboration ,collaborative coevolutionary algorithm ,combinational optimization ,consistent sublots ,cutting-tool degradation ,demanufacturing ,differential evolution algorithm ,disassembly line balancing ,disassembly planning ,emergency material distribution ,energy efficiency ,exact algorithm ,express packaging ,flexible job shop scheduling ,flexible manufacturing cell ,genetic algorithm ,green reverse logistics ,hybrid energy-saving strategy ,hybrid flowshop scheduling ,location-inventory-routing optimization ,machine tool turning-on/off schedule ,mixed integer linear programming ,mixed-model ,multi-objective ,multi-objective optimization ,multi-period ,multi-period demand ,municipal solid waste ,partial destructive mode ,perishable materials ,reduce carbon emissions ,remanufacturing ,reverse logistics ,robust optimization ,sustainable logistics ,synchronization ,two-sided ,uncertain demand ,variable neighborhood descent ,waste classification ,waste collection and transportation ,waste logistics ,whale optimization algorithm - Abstract
Summary: To address the increasingly prominent environmental pollution and energy shortage, many countries devote themselves to green manufacturing and logistics in which some optimization problems are common and challenging, e.g., production planning and scheduling, supply chain management, location and allocation problems, vehicle routing problem, resource optimization, and pricing strategies. The present reprint contains all of the articles accepted and published in the Special Issue "Mathematical Modeling and Intelligent Optimization in Green Manufacturing & Logistics" from the MDPI Mathematics journal. This Special Issue is focused on collecting recent mathematical modeling and intelligent optimization research in green manufacturing and logistics, including operations research, game theory, (meta)heuristics, machine learning, knowledge-driven, digital twin, and so on. We hope that the scientific results presented in this reprint will serve as a valuable source of documentation and inspiration to those researching the modeling and optimization of green manufacturing and sustainable logistics.