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Supporting multi-depot and stochastic waste collection management in clustered urban areas via simulation–optimization
- Source :
- Journal of Simulation. 11:11-19
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- Waste collection is one of the most critical logistics activities in modern cities with considerable impact on the quality of life, urban environment, city attractiveness, traffic flows and municipal budgets. Despite the problem’s relevance, most existing work addresses simplified versions where container loads are considered to be known in advance and served by a single vehicle depot. Waste levels, however, cannot be estimated with complete certainty as they are only revealed at collection. Furthermore, in large cities and clustered urban areas, multiple depots from which collection routes originate are common, although cooperation among vehicles from different depots is rarely considered. This paper analyses a rich version of the waste collection problem with multiple depots and stochastic demands by proposing a hybrid algorithm combining metaheuristics with simulation. Our ‘simheuristic’ approach allows for studying the effects of cooperation among different depots, thus quantifying the potential savings this cooperation could provide to city governments and waste collection companies.
- Subjects :
- 502017 Logistik
Operations research
Computer science
0211 other engineering and technologies
simheuristic
simulation-optimization
Waste collection
02 engineering and technology
waste collection management
101015 Operations Research
horizontal cooperation
0202 electrical engineering, electronic engineering, information engineering
Single vehicle
stochastic demand
Relevance (information retrieval)
Metaheuristic
Simulation optimization
021103 operations research
Hybrid algorithm
multi-depot vehicle routing problem
Work (electrical)
Modeling and Simulation
502017 Logistics
Container (abstract data type)
020201 artificial intelligence & image processing
Software
Subjects
Details
- ISSN :
- 17477786 and 17477778
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Journal of Simulation
- Accession number :
- edsair.doi.dedup.....e6d5d887c8b2333442401ae9db1fa541