A Hybrid Algorithm for Supply Chain Optimization
Ahmed Mohamed Ramzy;
Abstract
In this thesis, we review the current development and issues pertaining to supply chain optimization. A new practical model for optimizing the supply chain was developed and presented alongside with the solution algorithm. The model identifies within a set of potential plant and warehouse locations the best achievable supply chain design within reasonable time. The supply chain model used in our research is a four echelon model.
To solve the mathematical model more efficiently, we propose an effective heuristic method using Genetic Algorithm (GA). Although GA generally does not guarantee the optimal solution, the best heuristic solutions obtained in this study are consistent with the optimal solutions obtained using CPLEX solver (ver. 11.1). The implementation of GA that we describe here first employs an optimization-based heuristic to generate a connected path for each chromosome in the population and then employs genetic operators guided by the GA global optimization framework. The overall process is implemented using visual C# programming language.
Our computational results demonstrate that for large-scale •supply chain design problems, the proposed algorithm can substantially outperform general purpose combinatorial optimizers such as the branch-and-cut solver within CPLEX.
This thesis is structured into seven chapters, chapter 1 is a general introduction, we devote chapter 2 to discuss basic concepts in supply chain and supply chain management, at first, we differentiate between supply chain management and logistics, then, we introduce decision levels and supply chain drivers, philosophical origins of integration and integration supporting technologies, finally, we discuss recent concerns beyond integration. Chapter 3 is a review and survey of literature about supply chain modeling, location models and common solution approaches. In chapter 4, evolutionary algorithms are introduced briefly, and then genetic algorithms are discussed and followed by why they are criticized. Chapter 5 is dedicated for problem description, assumptions and mathematical model formulation. In chapter 6 the solution algorithm is presented, followed by a description of the computational experiments and a discussion of test results. Finally, we conclude by chapter 7 and identify directions for further research.
To solve the mathematical model more efficiently, we propose an effective heuristic method using Genetic Algorithm (GA). Although GA generally does not guarantee the optimal solution, the best heuristic solutions obtained in this study are consistent with the optimal solutions obtained using CPLEX solver (ver. 11.1). The implementation of GA that we describe here first employs an optimization-based heuristic to generate a connected path for each chromosome in the population and then employs genetic operators guided by the GA global optimization framework. The overall process is implemented using visual C# programming language.
Our computational results demonstrate that for large-scale •supply chain design problems, the proposed algorithm can substantially outperform general purpose combinatorial optimizers such as the branch-and-cut solver within CPLEX.
This thesis is structured into seven chapters, chapter 1 is a general introduction, we devote chapter 2 to discuss basic concepts in supply chain and supply chain management, at first, we differentiate between supply chain management and logistics, then, we introduce decision levels and supply chain drivers, philosophical origins of integration and integration supporting technologies, finally, we discuss recent concerns beyond integration. Chapter 3 is a review and survey of literature about supply chain modeling, location models and common solution approaches. In chapter 4, evolutionary algorithms are introduced briefly, and then genetic algorithms are discussed and followed by why they are criticized. Chapter 5 is dedicated for problem description, assumptions and mathematical model formulation. In chapter 6 the solution algorithm is presented, followed by a description of the computational experiments and a discussion of test results. Finally, we conclude by chapter 7 and identify directions for further research.
Other data
| Title | A Hybrid Algorithm for Supply Chain Optimization | Other Titles | خوارزم هجين لحل أمثلية مشكلة سلسلة الإمداد | Authors | Ahmed Mohamed Ramzy | Issue Date | 2010 |
Recommend this item
Similar Items from Core Recommender Database
Items in Ain Shams Scholar are protected by copyright, with all rights reserved, unless otherwise indicated.