Study on efficient planning for advanced logistics network model based on robust genetic algorithm

制度:新 ; 報告番号:甲3000号 ; 学位の種類:博士(工学) ; 授与年月日:2010/2/22 ; 早大学位記番号:新525

HOPX Crossover Operator for the Fixed Charge Logistic Model with Priority Based Encoding

In this paper, we are interested to an important Logistic problem modelised us optimization problem. It is the fixed charge transportation problem (FCTP) where the aim is to find the optimal solution which minimizes the objective function containig two costs, variable costs proportional to the amount shipped and fixed cost regardless of the quantity transported. To solve this kind of problem, metaheuristics and evolutionary methods should be applied. Genetic algorithms (GAs) seem to be one of such hopeful approaches which is based both on probability operators (Crossover and mutation) responsible for widen the solution space. The different characteristics of those operators influence on the performance and the quality of the genetic algorithm. In order to improve the performance of the GA to solve the FCTP, we propose a new adapted crossover operator called HOPX with the priority-based encoding by hybridizing the characteristics of the two most performent operators, the Order Crossover (OX) and Position-based crossover (PX). Numerical results are presented and discussed for several instances showing the performance of the developed approach to obtain optimal solution in reduced time in comparison to GAs with other crossover operators

A modified priority-based encoding for design of a closed-loop supply chain network using a discrete league championship algorithm

In a closed-loop supply chain network, the aim is to ensure a smooth fow of materials and attaining the maximum value from returning and end-of-life goods. Tis paper presents a single-objective deterministic mixed integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design problem consisting of plants, collection centers, disposal centers, and customer zones. Our model minimizes the total costs comprising fxed opening cost of plants, collection, disposal centers, and transportation costs of products among the nodes. As supply chain network design problems belong to the class of NP-hard problems, a novel league championship algorithm (LCA) with a modifed priority-based encoding is applied to fnd a near-optimal solution. New operators are defned for the LCA to search the discrete space. Numerical comparison of our proposed encoding with the existing approaches in the literature is indicative of the high quality performance of the proposed encoding

A modified priority-based encoding for design of a closed-loop supply chain network using a discrete league championship algorithm

In a closed-loop supply chain network, the aim is to ensure a smooth fow of materials and attaining the maximum value from returning and end-of-life goods. Tis paper presents a single-objective deterministic mixed integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design problem consisting of plants, collection centers, disposal centers, and customer zones. Our model minimizes the total costs comprising fxed opening cost of plants, collection, disposal centers, and transportation costs of products among the nodes. As supply chain network design problems belong to the class of NP-hard problems, a novel league championship algorithm (LCA) with a modifed priority-based encoding is applied to fnd a near-optimal solution. New operators are defned for the LCA to search the discrete space. Numerical comparison of our proposed encoding with the existing approaches in the literature is indicative of the high quality performance of the proposed encoding

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

Use Of Genetic Algorithms in Supply Chain Management. Literature Review and Current Trends

For the past few decades SCM has been one of the main objectives in research and practice. Since that time researchers have developed a lot of methods and procedures which optimized this process. To create an efficient supply chain network the resources and factories must be tightly integrated. The most supply chain network designs have multiple layers, members, periods, products, and comparative resources constraints exist between different layers. Supply chain networks design is related to the problems which are very popular in literature. The subject of this paper is to present the variants, configurations and parameters of genetic algorithm (GA) for solving supply chain network design problems. We focus on references from 2000 to 2011. Furthermore, current trends are introduced and discussed