Apply Algorithm with Mathematical Planning Optimization to Multi-Objective Problem

• Main Authors: Huang-Yu, Lin, 林煌諭
• Other Authors: Yu-Hsin, Chen
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/62986870762812666086

碩士 === 中原大學 === 工業與系統工程研究所 === 105 === The Metaheuristics has been developing for more than 50 years since the 1960s, made important contribution to NP-hard problem. The heuristic algorithm has a good solution in limited time but human face of the problem is no longer a single problem, but with many contradictions and related issues, the answer is no longer a single choice but multiple choice, although algorithm find the way to resolve multi-objective problem, it is not effective method. With the advance of mathematical methods, multi-objective problem is resolved by Systematic method. But mathematical methods need enormous time to resolve and has incompatibility with nonlinear programming. While heuristic algorithms are easy to deal with different frameworks, they can also get a good answer within a limited time, but at the same time lack a systematic way to solve the problem. This study enlightened by mathematical methods to construct a new multi-objective metaheuristics, the algorithm can divide the problem into multiple stages and regions by divide and conquer systematically and combine these solutions for improve the search ability of the algorithm. Through the concept of Pareto optimal solution to resolve multi-objective quadratic assignment problem and measured algorithm’s state and performance by the generally acknowledged performance indicators in Academics. Keyword: multi-objective, quadratic assignment problem, Pareto optimal solution, Ant Colony Optimization, Tabu Search