Adaptive Large Neighborhood Search for Scheduling of Mobile Robots
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00109329" target="_blank" >RIV/00216224:14330/19:00109329 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/citation.cfm?doid=3321707.3321764" target="_blank" >https://dl.acm.org/citation.cfm?doid=3321707.3321764</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3321707.3321764" target="_blank" >10.1145/3321707.3321764</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive Large Neighborhood Search for Scheduling of Mobile Robots
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The Genetic and Evolutionary Computation Conference (GECCO)
ISBN
9781450361118
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
224-232
Publisher name
ACM
Place of publication
New York, NY, USA
Event location
New York, NY, USA
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000523218400029