Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches
1st Edition
Published on 30. July 2025
Book
Paperback/Softback
174 pages
978-1-032-63439-5 (ISBN)
Description
This book introduces and analyses recent trends and studies of sustainable logistics systems using AI-based meta-heuristics approaches, including AI-based meta-heuristics applied to supply chain network models, integrated multi-criteria decision-making approaches for green supply chain management, uncertain supply chain models etc. It emphasizes both theory and practice, providing methodological and theoretical basis as well as case references for sustainable logistics systems using AI based meta-heuristics.
Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.
The chapters in this book were originally published in the International Journal of Management Science and Engineering Management.
Most of multi-national enterprises today face the challenge of sustainable development for their logistics systems trying to meet or exceed customer expectations. Sustainable development attracts both researchers and industrial practitioners who are focused on the design and implementation of logistics system. AI-based meta-heuristics approaches has emerged as a capable method for quickly providing optimal or near-optimal solutions for the problems that exact optimization cannot solve. Recent advances in various AI-based meta-heuristics approaches can resolve various and complex logistics and supply chain problem types. This book mainly encompasses the most popular and frequently employed AI-based meta-heuristics approaches such as genetic algorithm, variable neighborhood search, multi-objective heuristic search and the hybrid of these approaches.
The chapters in this book were originally published in the International Journal of Management Science and Engineering Management.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Postgraduate, Undergraduate Advanced, and Undergraduate Core
Dimensions
Height: 297 mm
Width: 210 mm
Thickness: 10 mm
Weight
504 gr
ISBN-13
978-1-032-63439-5 (9781032634395)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jiuping Xu | Mitsuo Gen | Zongmin Li
Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches
Book
12/2023
1st Edition
Routledge
€230.27
Shipment within 10-20 days
Jiuping Xu | Mitsuo Gen | Zongmin Li
Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches
E-Book
12/2023
1st Edition
Taylor & Francis
€60.49
Available for download
Jiuping Xu | Mitsuo Gen | Zongmin Li
Sustainable Logistics Systems Using AI-based Meta-Heuristics Approaches
E-Book
12/2023
1st Edition
Taylor & Francis
€60.49
Available for download
Persons
Jiuping Xu is Associate Vice President of Sichuan University, P.R. China, and Editor-in-Chief of International Journal of Management Science and Engineering Management. His research interests include decision science, engineering management, and management science.
Mitsuo Gen is Senior Research Scientist of Fuzzy Logic Systems Institute and Visiting Professor at Tokyo University of Science, Japan. His research interests include soft computing, evolutionary algorithms, intelligent manufacturing, and sustainable closed supply chain.
Zongmin Li is Professor of Business School, Sichuan University, P. R. China, and Managing Editor of International Journal of Management Science and Engineering Management. Her research interests include data-driven decision making and big data analytics.
YoungSu Yun is Professor of Division of Business Administration at Chosun University, South Korea. His research interests include sustainable closed supply chain system, engineering optimization design and evolutionary algorithms.
Mitsuo Gen is Senior Research Scientist of Fuzzy Logic Systems Institute and Visiting Professor at Tokyo University of Science, Japan. His research interests include soft computing, evolutionary algorithms, intelligent manufacturing, and sustainable closed supply chain.
Zongmin Li is Professor of Business School, Sichuan University, P. R. China, and Managing Editor of International Journal of Management Science and Engineering Management. Her research interests include data-driven decision making and big data analytics.
YoungSu Yun is Professor of Division of Business Administration at Chosun University, South Korea. His research interests include sustainable closed supply chain system, engineering optimization design and evolutionary algorithms.
Content
Introduction - Sustainable Logistics Systems using AI-based Meta-Heuristics Approaches 1. Applying GA-VNS approach to supply chain network model with facility and route disruptions 2. Edge boundary variable neighborhood strategy adaptive search for a vegetable crop land allocation problem 3. Multi-criteria decision-making methods for the evaluating of a real green supply chain in companies with fast-moving consumer goods 4. Multi-objective grouping genetic algorithm for the joint order batching, batch assignment, and sequencing problem 5. Green supply chain management framework for supplier selection: an integrated multi-criteria decision-making approach 6. A dynamic multi-objective green supply chain network design for perishable products in uncertain environments, the coffee industry case study 7. Robust and resilient supply chain network design considering risks in food industry: flavour industry in Iran 8. Modeling resilient supplier selection criteria in desalination supply chain based on fuzzy DEMATEL and ISM 9. Designing a data-driven leagile sustainable closed-loop supply chain network 10. Designing an integrated decision support system to link supply chain processes performance with time to market 11. Application of expected value and chance constraint on uncertain supply chain model with cost, risk and visibility for COVID-19 pandemic 12. Optimal storage and shipment management of perishable agri-products with a hybrid priority policy: a case study