A hybrid genetic Tabu search algorithm for minimising total completion time in a flexible job-shop scheduling problem

2020 ◽  
Vol 14 (6) ◽  
pp. 763
Author(s):  
Asma Fekih ◽  
Hatem Hadda ◽  
Imed Kacem ◽  
Atidel B. Hadj Alouane
Keyword(s):  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Flexible Job Shop ◽  
Tabu Search Algorithm ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling

Petri Net with Uncontrollable Transition and GA Based Approach for JSP

2011 ◽  
Vol 48-49 ◽  
pp. 824-829
Author(s):  
Tao Ze ◽  
Xiao Xia Liu
Keyword(s):  
Petri Net ◽  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Scheduling Method

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) with urgent orders constrained by machines, workers. Firstly, a controller designed method for Petri net with uncontrollable transition is introduced, and based on the method, the Petri net model is constructed for urgent jobs in flexible job shop scheduling problem. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Function objectives of the proposed method are to minimize the completion time and the total expense of machines and workers. Finally, Scheduling example is employed to illustrate the effectiveness of the method.

scholarly journals A global-local neighborhood search algorithm and tabu search for flexible job shop scheduling problem

2021 ◽  
Vol 7 ◽  
pp. e574
Author(s):  
Nayeli Jazmin Escamilla Serna ◽  
Juan Carlos Seck-Tuoh-Mora ◽  
Joselito Medina-Marin ◽  
Norberto Hernandez-Romero ◽  
Irving Barragan-Vite ◽  
...  
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Neighborhood Search Algorithm

The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called smart-cells generates and shares information that helps to optimize instances of the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms, using four benchmark sets and 101 test problems.

scholarly journals Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Behnam Barzegar ◽  
Homayun Motameni ◽  
Hossein Bozorgi
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Gravitational Search

Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN) that is based on gravitational search algorithm (GSA). In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

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