A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty |
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| Authors: | Inés González-Rodríguez Camino R Vela Jorge Puente |
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| Affiliation: | 1. Department of Mathematics, Statistics and Computing, University of Cantabria, Los Castros s/n, Santander, 39005, Spain
2. A.I. Centre and Department of Computer Science, University of Oviedo, Campus de Viesques s/n, Gijón, 33271, Spain
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| Abstract: | In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations
are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on
lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching
in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the
GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate
the potential of the proposed multiobjective model and genetic algorithm. |
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