Genetic Algorithm and Particle Swarm Optimization Techniques for Solving Multi-Objectives on Single Machine Scheduling Problem

Autor:	Hanan Ali Chachan, Alaa Sabah Hameed
Rok vydání:	2020
Předmět:	Mathematical optimization Single-machine scheduling Branch and bound Computer science Tardiness Particle swarm optimization Completion time Scheduling (computing)
Zdroj:	Ibn AL- Haitham Journal For Pure and Applied Sciences. 33:119
ISSN:	2521-3407 1609-4042
DOI:	10.30526/33.1.2378
Popis:	In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7d7a30a366fce4765567d8509449fb46 https://doi.org/10.30526/33.1.2378 Zobrazit plný text záznamu