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https://ptsldigital.ukm.my/jspui/handle/123456789/513491Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Salwani Abdullah, Assoc. Prof. Dr. | |
| dc.contributor.author | Majid Abdolrazzagh Nezhad (P52865) | |
| dc.date.accessioned | 2023-10-16T04:37:14Z | - |
| dc.date.available | 2023-10-16T04:37:14Z | - |
| dc.date.issued | 2013-06-19 | |
| dc.identifier.other | ukmvital:75027 | |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/513491 | - |
| dc.description | Job-shop scheduling problems (JSSP) as a NP-hard problem is the most important timely decision in industry and its constraints are frequently imprecise in the real world such as uncertain due dates and vague processing times. It deals with the assignment of jobs to machines. Many exact and approximation algorithms have been proposed to solve the JSSP by previous researchers during the past four decades. Currently, the efforts have been focused on meta-heuristic algorithms. The construction of the JSSP has been done by various methods such as random methods, priority rules and the heuristic algorithms. Based on the published literature, most previous researchers have used random techniques such as random keys to produce the initial population. This technique has a number of disadvantages, such as a high probability of generating infeasible points, quality of points is far below that of optimal points, and takes longer time to reach the optimal solution than algorithms that use guided techniques in their initialization algorithm. Finding a desirable initial population is an NP-hard problem because the space solution of the JSSP is complex and has a very high number of points , where is the number of jobs and equals the number of machine. In this thesis, novel meta-heuristic construction algorithms are proposed to generate initial solution near to the optimal solution in an acceptably short computation time for crisp and fuzzy JSSP (with fuzzy processing time and fuzzy due date). Two types of constructive algorithms with and without random selections are proposed (coded as CA2 and CA1, respectively). These algorithms are planned based on skipping strategies i.e., a process of moving from primal point to a better point. In CA1, two skipping strategies are introduced referred as RDOSS (Reduce the Distance of Operations from the Sources and the Sinks) and the FGSF (Fill up the Gaps into the Switching Function Algorithm). While in CA2, three skipping strategies are proposed i.e., SMHT (Shorten the Maximum Head and Tail paths), ISS-FGR (Intelligent Skipping Strategy based on the First Generation-Rules of mPlates-Jobs) and ISS-SGR (Intelligent Skipping Strategy based on the Second Generation-Rules of mPlates-Jobs). The produced initial population for crisp and fuzzy JSSP is further improved by the basic Electromagnetic-like Mechanism (EM) and an enhanced version of EM that employs a multi-memorized movement and a new intelligent local search. The experimental results show that the proposed algorithms have significantly improved the convergence speed that leads to a better solution quality. Overall comparisons indicate that the proposed approach works well across all datasets and able to obtain a number of best results in comparison with best known results in the literature.,PhD | |
| dc.language.iso | eng | |
| dc.publisher | UKM, Bangi | |
| dc.relation | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
| dc.rights | UKM | |
| dc.subject | Initialization Heuristics With Electromagnetic-Like Mechanism | |
| dc.subject | Heuristics With Electromagnetic-Like Mechanism For Crisp Job Shop Scheduling Problems | |
| dc.subject | Heuristics With Electromagnetic-Like Mechanism For Fuzzy Job Shop Scheduling Problems | |
| dc.subject | Neural networks (Computer science) | |
| dc.title | Initialization Heuristics With Electromagnetic-Like Mechanism For Crisp And Fuzzy Job Shop Scheduling Problems | |
| dc.type | Theses | |
| dc.format.pages | 321 | |
| dc.identifier.callno | QA76.87 .N496 2013 | |
| dc.identifier.barcode | 000209 | |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_75027+Source01+Source010.PDF Restricted Access | 8.21 MB | Adobe PDF |  View/Open |
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