Tardiness Minimisation for Job Shop Scheduling with Interval Uncertainty
| Autor: | Camino R. Vela, Hernán Díaz, Irene Díaz, Inés González-Rodríguez, Juan José Palacios |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Job shop scheduling Computer science Tardiness Interval uncertainty 02 engineering and technology Genetic algorithms Job shop scheduling problem Job Shop Scheduling Minimisation (clinical trials) Total tardiness Optimization systems theory Manufacturing engineering 020901 industrial engineering & automation Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Robustness |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030617042 HAIS RUO. Repositorio Institucional de la Universidad de Oviedo instname |
| DOI: | 10.1007/978-3-030-61705-9_18 |
| Popis: | International Conference Hybrid Artificial Intelligent Systems. HAIS 2020 (15th. 2020. Gijón, Spain) This paper considers the interval job shop scheduling problem, a variant of the deterministic problem where task durations and due dates are uncertain and modelled as intervals. With the objective of minimising the total tardiness with respect to due dates, we propose a genetic algorithm. Experimental results are reported to assess its behaviour and compare it with the state-of-the-art algorithms, showing its competitiveness. Additional results in terms of solution robustness are given to illustrate the relevance of the interval ranking method used to compare schedules as well as the benefits of taking uncertainty into account during the search process. Supported by the Spanish Government under research grants TIN2016-79190-R and TIN2017-87600-P and by the Principality of Asturias Government under grant IDI/2018/000176. |
| Databáze: | OpenAIRE |
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