GRASP to minimize makespan for a capacitated batch-processing machine
में बचाया:
| में प्रकाशित: | The International Journal of Advanced Manufacturing Technology vol. 68, no. 1-4 (Sep 2013), p. 407 |
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| मुख्य लेखक: | |
| अन्य लेखक: | , |
| प्रकाशित: |
Springer Nature B.V.
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| विषय: | |
| ऑनलाइन पहुंच: | Citation/Abstract Full Text - PDF |
| टैग: |
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| 024 | 7 | |a 10.1007/s00170-013-4737-z |2 doi | |
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| 045 | 2 | |b d20130901 |b d20130930 | |
| 100 | 1 | |a Damodaran, Purushothaman |u Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, IL, USA | |
| 245 | 1 | |a GRASP to minimize makespan for a capacitated batch-processing machine | |
| 260 | |b Springer Nature B.V. |c Sep 2013 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper presents a Greedy Randomized Adaptive Search Procedure (GRASP) to minimize the makespan of a capacitated batch-processing machine. Given a set of jobs and their processing times and sizes, the objective is to group these jobs into batches and schedule the batches on a single batch-processing machine such that the time taken to complete the last batch of jobs (or makespan) is minimized. The batch-processing machine can process a batch of jobs simultaneously as long as the total size of all the jobs in that batch does not exceed the machine capacity. The batch-processing time is equal to the longest processing time for a job in the batch. It has been shown that the problem under study is non-deterministic polynomial-time hard. Consequently, a GRASP approach was developed. The solution quality of GRASP was compared to other solution approaches such as simulated annealing, genetic algorithm, and a commercial solver through an experimental study. The study helps to conclude that GRASP outperforms other solution approaches, especially on larger problem instances. | |
| 653 | |a Production scheduling | ||
| 653 | |a Batch processing | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Simulated annealing | ||
| 653 | |a Sequential scheduling | ||
| 653 | |a Adaptive search techniques | ||
| 653 | |a Computer simulation | ||
| 653 | |a Polynomials | ||
| 653 | |a Schedules | ||
| 700 | 1 | |a Ghrayeb, Omar |u Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, IL, USA | |
| 700 | 1 | |a Guttikonda, Mallika Chowdary |u Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, IL, USA | |
| 773 | 0 | |t The International Journal of Advanced Manufacturing Technology |g vol. 68, no. 1-4 (Sep 2013), p. 407 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2262369827/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2262369827/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |