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This educational guide will help students and practitioners seeking to understand the fundamentals and practice of linear programming. The exercises contained within demonstrate how to solve classical optimization problems with an emphasis on spatial analysis in supply chain management and transport logistics. All exercises describe the Python programs and optimization libraries that can be used to solve them. The first chapter introduces key concepts in linear programming and establishes a new cognitive framework to help students and practitioners set up each optimization problem. This cognitive framework organizes the decision variables, constraints, objective function, and variable bounds in a format that allows for direct application to optimization software. The second chapter introduces two types of mobility optimization problems (shortest path in a network and minimum cost tour) in the context of delivery and service planning logistics. The third chapter introduces four types of spatial optimization problems (neighborhood coverage, flow capturing, zone heterogeneity, service coverage) and provides a workflow for visualizing the optimized solutions in maps. The workflow creates decision variables from maps by using the free geographic information systems (GIS) programs QGIS and GeoDA. The fourth chapter introduces three types of spatial logistics problems (spatial distribution, flow maximization, warehouse location optimization) and demonstrates how to scale the cognitive framework in software to reach solutions. The final chapter summarizes lessons learned and provides insights about how students and practitioners can modify the Python programs and GIS workflows to solve their own optimization problem and visualize the results.
Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities. Logistics and transportation problems are examined within a sustainability perspective to offer a comprehensive assessment of environmental, social, ethical, and economic performance measures. Featured models, techniques, and algorithms may be used to construct policies on alternative transportation modes and technologies, green logistics, and incentives by the incorporation of environmental, economic, and social measures. Researchers, professionals, and graduate students in urban regional planning, logistics, transport systems, optimization, supply chain management, business administration, information science, mathematics, and industrial and systems engineering will find the real life and interdisciplinary issues presented in this book informative and useful.
Solving Transport Problems establishes fundamental points and good practice in resolving matters regarding green transportation. This is to prompt further research in conveyance issues by providing readers with new knowledge and grounds for integrated models and solution methods. Focusing on green transportation, this book covers various sub-topics and thus consists of diverse content. Traditionally, academia and transport practitioners have mainly concentrated on efficient fleet management to achieve economic benefits and better-quality service. More recently, due to growing public environmental concerns and the industry understanding of the issue, the academic community has started to address environmental issues. The studies of green transportation compiled in this book have identified certain areas of interest, such as references, viewpoints, algorithms and ideas. Solving Transport Problems is for researchers, environmental decision-makers and other concerned parties, to start discussion on developing optimized technology and alternative fuel-based integrated models for environmentally cleaner transport systems.
This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.
Thecontentofthisbookismotivatedbytherecentchangesinglobalmarketsandthe availability of new transportation services. Indeed, the complexity of current supply chains suggests todecision makers in logisticsto work witha set ofef?cient (Pare- optimal) solutions, mainly to capture different economical aspects that, in general, one optimal solution related to a single objective function is not able to capture - tirely. Motivated by these reasons, we study freight transportation systems with a speci?c focus on multi-objective modelling. The goal is to provide decision m- ers with new methods and tools to implement multi-objective optimization models in logistics. The book combines theoretical aspects with applications, showing the advantages and the drawbacks of adopting scalarization techniques, and when it is worthwhile to reduce the problem to a goal-programming one. Also, we show - plications where more than one decision maker evaluates the effectiveness of the logistic system and thus a multi-level programming is sought to attain meaningful solutions. After presenting the general working framework, we analyze logistic - sues in a maritime terminal. Next, we study multi-objective route planning, relying on the application of hazardous material transportation. Then, we examine freight distribution on a smaller scale, as for the case of goods distribution in metropolitan areas. Finally, we present a human-workforce problem arising in logistic platforms. The general approach followed in the text is that of presenting mathematics, al- rithms and the related experimentations for each problem.
In a world with highly competitive markets and economic instability due to capitalization, industrial competition has increasingly intensified. In order for many industries to survive and succeed, they need to develop highly effective coordination between supply chain partners, dynamic collaborative and strategic alliance relationships, and efficient logistics and supply chain network designs. Consequently, in the past decade, there has been an explosion of interest among academic researchers and industrial practitioners in innovative supply chain and logistics models, algorithms, and coordination policies. Mathematically distinct from classical supply chain management, this emerging research area has been proven to be useful and applicable to a wide variety of industries. This book brings together recent advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise.
The second edition of Multi-Objective Management in Freight Logistics builds upon the first, providing a detailed study of freight transportation systems, with a specific focus on multi-objective modelling. It offers decision-makers methods and tools for implementing multi-objective optimisation models in logistics. The second edition also includes brand-new chapters on green supply chain and hybrid fleet management problems. After presenting the general framework and multi-objective optimization, the book analyses green logistic focusing on two main aspects: green corridors and network design; next, it studies logistic issues in a maritime terminal and route planning in the context of hazardous material transportation. Finally, heterogeneous fleets distribution and coordination models are discussed. The book presents problems providing the mathematics, algorithms, implementations, and the related experiments for each problem. It offers a valuable resource for postgraduate students and researchers in transportation, logistics and operations, as well as practitioners working in service systems.
Logistics and transportation are a complex set of entities and systems interconnected by many physical, financial, and information flows, and, as with all systems, there are optimization and planning issues. In addition, they are subject to economic, social, and especially environmental pressures with the need to reduce energy consumption and greenhouse gas emissions. There is a need for original research to address these issues. Transport and Logistics Planning and Optimization addresses selected transportation and logistics problems at the strategic, tactical, and operational levels in a multidisciplinary approach, not only from a technological perspective but also from a social science perspective. Covering key topics such as supply chain, urban transportation, artificial intelligence, and computer science, this premier reference source is ideal for policymakers, industry professionals, researchers, academicians, scholars, instructors, and students.
This book is the collection of my own studies in the optimization of logistics and supply chain systems, targeted to a broad readership. In this book, first few chapters of the optimization concepts come out of the materials I used to refer while doing my research. I brought together some of these materials to form a guidance material on the fundamentals of the optimization concepts along with my own studies in the application of optimization methods. For a macro level logistics and supply chain systems optimization perspective, I added several chapters that are the results of my studies, which use the Global Trade Analysis Project (GTAP and GDyn) simulations. The static and dynamic computable general equilibrium (CGE) concept is also the essential part of the optimization study of logistics and supply chain systems. Therefore, the fundamentals of the static and dynamic (CGE) models are introduced. As the demand for logistics depends mostly on the volume of trade and trade patterns, international trade affects the transport and logistics, as it might generate a higher or lower demand for transport and logistics services, which are calculated by various approaches of optimization studies. This book consists of six parts and twenty chapters. The first part of the book, which includes three chapters, is about introduction to optimization with typical base problems and algorithms for solving these problems. The second part of this book includes five my own researches in the application of optimization methods. The third part of the book shortly introduces you to the general concepts of the computable general equilibrium models (CGE) and presents you the fundamentals of a CGE model. In each chapter of the fourth part, short articles that include five simulations based on various scenarios are presented. The fifth part of the book briefly introduces you to the basic concepts of the computable general equilibrium models (CGE) and then, presents you the fundamentals of dynamic general equilibrium models. In each chapter of the sixth part, two short articles that simulate various scenarios are presented. All the chapters in this book are independent of each other. I hope you will find this book informative, beneficial and appropriate for your needs.
In a context of global competition, the optimization of logistics systems is inescapable. Logistics Systems: Design and Optimization falls within this perspective and presents twelve chapters that well illustrate the variety and the complexity of logistics activities. Each chapter is written by recognized researchers who have been commissioned to survey a specific topic or emerging area of logistics. The first chapter, by Riopel, Langevin, and Campbell, develops a framework for the entire book. It classifies logistics decisions and highlights the relevant linkages to logistics decisions. The intricacy of these linkages demonstrates how thoroughly the decisions are interrelated and underscores the complexity of managing logistics activities. Each of the chapters focus on quantitative methods for the design and optimization of logistics systems.