Reprint

Mathematical Modeling and Intelligent Optimization in Green Manufacturing & Logistics

Edited by
May 2023
236 pages
  • ISBN978-3-0365-7570-4 (Hardback)
  • ISBN978-3-0365-7571-1 (PDF)

This book is a reprint of the Special Issue Mathematical Modeling and Intelligent Optimization in Green Manufacturing & Logistics that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Public Health & Healthcare
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.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
auto parts supply chain; sustainable logistics; robust optimization; location-inventory-routing optimization; multi-period demand; emergency material distribution; multi-period; uncertain demand; perishable materials; whale optimization algorithm; differential evolution algorithm; AGV scheduling; flexible manufacturing cell; AGV charging; genetic algorithm; municipal solid waste; waste classification; waste logistics; waste collection and transportation; IoT; cloud-edge collaboration; synchronization; demanufacturing; disassembly planning; asynchronous parallel disassembly; mixed integer linear programming; exact algorithm; hybrid flowshop scheduling; energy efficiency; consistent sublots; collaborative coevolutionary algorithm; variable neighborhood descent; reverse logistics; remanufacturing; EOL product; combinational optimization; cutting-tool degradation; machine tool turning-on/off schedule; hybrid energy-saving strategy; multi-objective optimization; flexible job shop scheduling; express packaging; green reverse logistics; reduce carbon emissions; K-means algorithm; bi-objective model; NSGA-II algorithm; multi-objective; mixed-model; two-sided; disassembly line balancing; partial destructive mode