Minimizing the total completion time and total earliness time functions for a machine scheduling problem using local search methods

9Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems 1//(∑Cj ∑Ej) and 1//∑Cj + ∑Ej. The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.

Cite

CITATION STYLE

APA

Ali, F. H., & Jawad, A. A. (2020). Minimizing the total completion time and total earliness time functions for a machine scheduling problem using local search methods. Iraqi Journal of Science, 2020, 126–133. https://doi.org/10.24996/ijs.2020.SI.1.17

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free