scholarly journals Heuristics and stochastic local search for just-in-time scheduling of parallel machines against common restrictive due windows

Author(s):  
Gustavo Alencar Rolim
2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Sivashan Chetty ◽  
Aderemi O. Adewumi

The Just-In-Time (JIT) scheduling problem is an important subject of study. It essentially constitutes the problem of scheduling critical business resources in an attempt to optimize given business objectives. This problem is NP-Hard in nature, hence requiring efficient solution techniques. To solve the JIT scheduling problem presented in this study, a new local search metaheuristic algorithm, namely, the enhanced Best Performance Algorithm (eBPA), is introduced. This is part of the initial study of the algorithm for scheduling problems. The current problem setting is the allocation of a large number of jobs required to be scheduled on multiple and identical machines which run in parallel. The due date of a job is characterized by a window frame of time, rather than a specific point in time. The performance of the eBPA is compared against Tabu Search (TS) and Simulated Annealing (SA). SA and TS are well-known local search metaheuristic algorithms. The results show the potential of the eBPA as a metaheuristic algorithm.


1991 ◽  
Vol 2 (4) ◽  
pp. 253-260 ◽  
Author(s):  
Manuel Laguna ◽  
Jos� Luis Gonz�lez Velarde

2009 ◽  
Vol 19 (3) ◽  
pp. 347-368 ◽  
Author(s):  
Yaron Leyvand ◽  
Dvir Shabtay ◽  
George Steiner ◽  
Liron Yedidsion

Omega ◽  
2016 ◽  
Vol 63 ◽  
pp. 41-47 ◽  
Author(s):  
Yunqiang Yin ◽  
Shuenn-Ren Cheng ◽  
T.C.E. Cheng ◽  
Du-Juan Wang ◽  
Chin-Chia Wu

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