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

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

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...

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Bibliographic Details
Main Authors: Alaa Sabah Hameed, Hanan Ali Chachan
Format: Article
Language:English
Published: University of Baghdad 2020-01-01
Series:Ibn Al-Haitham Journal for Pure and Applied Sciences
Subjects:
The Branch and Bound method (BAB), The Local search algorithms, The Genetic Algorithm (GA), The Particle swarm optimization (PSO), The Multi-Objective problems.
Online Access:https://jih.uobaghdad.edu.iq/index.php/j/article/view/2378

Internet

https://jih.uobaghdad.edu.iq/index.php/j/article/view/2378

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