Choosing efficient meta-heuristics to solve the assembly line balancing problem: A landscape analysis approach

被引：7

作者：

Nourmohammadi, Amir ^{[1
]}

Fathi, Masood ^{[1
]}

Ng, Amos H. C. ^{[1
]}

机构：

[1] Univ Skovde, Dept Prod & Automat Engn, POB 408, SE-54128 Skovde, Sweden

来源：

52ND CIRP CONFERENCE ON MANUFACTURING SYSTEMS (CMS) | 2019年 / 81卷

基金：

欧盟地平线“2020”;

关键词：

assembly line balancing; fitness landscape analysis; meta-heuristic algorithms; GENETIC ALGORITHM; DESIGN; MODEL;

D O I：

10.1016/j.procir.2019.03.302

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated. (C) 2019 The Authors. Published by Elsevier Ltd.

引用

收藏

页码：1248 / 1253

页数：6

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