To read this content please select one of the options below:

Hybrid approach for solving the integrated planning and scheduling production problem

Zineb Ibn Majdoub Hassani (Mechanical Engineering Laboratory, Faculty of Sciences and Technology of Fez, Fez, Morocco)
Abdellah El Barkany (Mechanical Engineering Laboratory, Faculty of Sciences and Technology of Fez, Fez, Morocco)
Abdelouahhab Jabri (Mechanical Engineering Laboratory, Faculty of Sciences and Technology of Fez, Fez, Morocco)
Ikram El Abbassi (LR2E, ECAM EPMI, Cergy-Pontoise, France)
Abdel Moumen Darcherif (ECAM EPMI, Cergy-Pontoise, France)

Journal of Engineering, Design and Technology

ISSN: 1726-0531

Article publication date: 4 September 2019

Issue publication date: 16 January 2020

217

Abstract

Purpose

This paper aims to present a new model for solving the integrated production planning and scheduling. Usually, the two decision levels are treated sequentially because of their complexity. Scheduling depends on the lot sizes calculated at the tactical level and ignoring scheduling constraints generates unrealistic and inconsistent decisions. Therefore, integrating more detail scheduling constraint in production planning is important for managing efficiently operations. Therefore, an integrated model was developed, and two evolutionary optimization approaches were suggested for solving it, namely, genetic algorithm (GA) and the hybridization of simulated annealing (SA) with GA HSAGA. The proposed algorithms have some parameters that must be adjusted using Taguchi method. Therefore, to evaluate the proposed algorithm, the authors compared the results given by GA and the hybridization. The SA-based local search is embedded into a GA search mechanism to move the GA away from being closed within local optima. The analysis shows that the combination of simulated annealing with GA gives better solutions and minimizes the total production costs.

Design/methodology/approach

The paper opted for an approached resolution method particularly GA and simulated annealing. The study represents a comparison between the results found using GA and the hybridization of simulated annealing and GA. A total of 45 instances were studied to evaluate job-shop problems of different sizes.

Findings

The results illustrate that for 36 instances of 45, the hybridization of simulated annealing and GA HSAGA has provided best production costs. The efficiency demonstrated by HSAGA approach is related to the combination between the exploration ability of GA and the capacity to escape local optimum of simulated annealing.

Originality/value

This study provides a new resolution approach to the integration of planning and scheduling while considering a new operational constrain. The model suggested aims to control the available capacity of the resources and guaranties that the resources to be consumed do not exceed the real availability to avoid the blocking that results from the unavailability of resources. Furthermore, to solve the MILP model, a GA is proposed and then it is combined to simulated annealing.

Keywords

Citation

Ibn Majdoub Hassani, Z., El Barkany, A., Jabri, A., El Abbassi, I. and Darcherif, A.M. (2020), "Hybrid approach for solving the integrated planning and scheduling production problem", Journal of Engineering, Design and Technology, Vol. 18 No. 1, pp. 172-189. https://doi.org/10.1108/JEDT-11-2018-0198

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

Related articles