Adaptive large neighborhood search for scheduling of mobile robots

Quang-Vinh Dang, Hana Rudová, Cong Thanh Nguyen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)
1 Downloads (Pure)


Our work addresses the scheduling of mobile robots for transportation and processing of operations on machines in a flexible manufacturing system. Both mobile robots and automated guided vehicles (AGVs) can transport components among machines in the working space. Nevertheless, the difference is that mobile robots considered in this work can process specific value-added operations, which is not possible for AGVs. This new feature increases complexity as well as computational demands. To summarize, we need to compute a sequence of operations on machines, the robot assignments for transportation, and the robot assignments for processing. The main contribution is the proposal of an adaptive large neighborhood search algorithm with the sets of exploration and exploitation heuristics to solve the problem considering makespan minimization. Experimental evaluation is presented on the existing benchmarks. The quality of our solutions is compared to a heuristic based on genetic algorithm and mixed-integer programming proposed recently. The comparison shows that our approach can achieve comparable results in real time which is in order of magnitude faster than the earlier heuristic.
Originele taal-2Engels
TitelGECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference
Plaats van productieNew York
UitgeverijAssociation for Computing Machinery, Inc
Aantal pagina's9
ISBN van geprinte versie978-1-4503-6111-8
StatusGepubliceerd - 13 jul. 2019
Evenement2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Tsjechië
Duur: 13 jul. 201917 jul. 2019


Congres2019 Genetic and Evolutionary Computation Conference, GECCO 2019


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