An Improved Tabu Search Algorithm for Job Shop Scheduling Problem Trough Hybrid Solution Representations
Authors
Abstract:
Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison with the existing ones
similar resources
An Advanced Tabu Search Algorithm for the Job Shop Problem
The job shop scheduling problem with the makespan criterion is a certain NP-hard case from OR theory having excellent practical applications. This problem, having been examined for years, is also regarded as an indicator of the quality of advanced scheduling algorithms. In this paper we provide a new approximate algorithm that is based on the big valley phenomenon, and uses some elements of so-...
full textAn algorithm for multi-objective job shop scheduling problem
Scheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we pro...
full textParallel tabu search for the cyclic job shop scheduling problem
In this paper, we consider a cyclic job shop problem, consisting of production of a certain set of elements at fixed intervals. Optimization of the process is reduced to a minimization of a cycle time, i.e. the time, after which the next batch of the same elements may be produced. We introduce a new parallel method for the cost function calculation. The parallelization is not trivial and cannot...
full textNew Tabu Search Results for the Job Shop Scheduling Problem
In the classical job shop scheduling problem (JSSP), n jobs are processed to completion on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. Processing times are sequence-independent, fixed, and known in advance. Each machine is continuously available fro...
full textProblem difficulty for tabu search in job-shop scheduling
Tabu search algorithms are among the most effective approaches for solving the job-shop scheduling problem (JSP). Yet, we have little understanding of why these algorithms work so well, and under what conditions. We develop a model of problem difficulty for tabu search in the JSP, borrowing from similar models developed for SAT and other NP-complete problems. We show that the mean distance betw...
full textAn Improved Tabu Search Approach for Solving the Job Shop Scheduling Problem with Tooling Constraints
Flexible manufacturing systems (FMSs) are nowadays installed in the mechanical industry. In such systems. many different part types are produced simultaneously and it is necessary to take tooling constraints into account for finding an optimal schedule. A heuristic method is presented for solving the m-machine, n-job shop scheduling problem with tooling constraints. This method. named TOMATO, i...
full textMy Resources
Journal title
volume 3 issue 1
pages 13- 26
publication date 2018-07-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023