Dynamic Monte-Carlo Tree Search Algorithm for Multi-Objective Flexible Job-shop Scheduling Problem

2016 ◽  
Vol 10 (4) ◽  
pp. 1531-1539 ◽  
Author(s):  
Chun-Liang Lu ◽  
Shih-Yuan Chiu ◽  
Jiinpo Wu ◽  
Li-Pen Chao
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Tree Search ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Monte Carlo Tree Search ◽  
Shop Scheduling ◽  
Dynamic Monte Carlo ◽  
Tree Search Algorithm

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.

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