Discrete Cuckoo Search Algorithm for Job Shop Scheduling Problem

被引：0

作者：

Ouaarab, Aziz ^{[1
]}

Ahiod, Belaid ^{[1
]}

Yang, Xin-She ^{[2
]}

Abbad, Mohammed ^{[1
]}

机构：

[1] Mohammed V Agdal Univ, Associated Unit CNRST URAC 29, LRIT, BP 1014, Rabat, Morocco

[2] Middlesex Univ, Sch Sci & Technol, Burroughs, London NW4 4BT, England

来源：

2014 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC) | 2014年

关键词：

Nature-Inspired Metaheuristic; Cuckoo Search; Levy Flights; Combinatorial Optimization; Job Shop Scheduling Problem; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an application of Discrete Cuckoo Search (DCS) algorithm for solving the Job Shop Scheduling Problem (JSSP), one of the most difficult NP-hard combinatorial optimization problems. DCS is recently developed by Ouaarab et al. in 2013, based on Cuckoo Search (CS), proposed by Yang and Deb in 2009. DCS performs its search via Levy flights by proposing three different steps to move in the search space. It applies a search balance between local and global random walk. The performance of DCS is tested on a set of benchmarks of JSSP from the OR-Library. The test results are compared with a Particle Swarm Optimization (PSO) algorithm and they showed that DCS outperforms PSO.

引用

页码：1872 / 1876

页数：5

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