A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions

Bibliographic Data

ID15479213
AuthorsHailin Wu (0000-0003-0239-5635, Chongqing University), Fengming Tao (0000-0001-9533-2005, Chongqing University, corresponding author), Qingqing Qiao (0000-0002-3638-4355, Chongqing University), Mengjun Zhang (0000-0002-4408-0677, Chongqing University)
Year2020
Volume17
Issue2
Pages458-458
Publication date2020-01-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17020458
PMID31936754
OpenAlexW3000035086
LanguageEN
Citations received4
References cited4

In order to solve the optimization problem of wet waste collection and transportation in Chinese cities, this paper constructs a chance-constrained low-carbon vehicle routing problem (CCLCVRP) model in waste management system and applies certain algorithms to solve the model. Considering the environmental protection point of view, the CCLCVRP model combines carbon emission costs with traditional waste management costs under the scenario of application of smart bins. Taking into the uncertainty of the waste generation rate, chance-constrained programming is applied to transform the uncertain model to a certain one. The initial optimal solution of this model is obtained by a proposed hybrid algorithm, that is, particle swarm optimization (PSO); and then the further optimized solution is obtained by simulated annealing (SA) algorithm, due to its global optimization capability. The effectiveness of PSOSA algorithm is verified by the classic database in a capacitated vehicle routing problem (CVRP). What's more, a case of waste collection and transportation is applied in the model for acquiring reliable conclusions, and the application of the model is tested by setting different waste fill levels (WFLs) and credibility levels. The results show that total costs rise with the increase of credibility level reflecting dispatcher's risk preference; the WFL value range between 0.65 and 0.75 can obtain the optimal solution under different credibility levels. Finally, according to these results, some constructive proposals are propounded for the government and the logistics organization dealing with waste collection and transportation

Algorithm · Credibility · Credibility theory · Fuzzy logic · Mathematical optimization · Municipal solid waste · Operations research · Particle swarm optimization · Routing (electronic design automation · Simulated annealing · Vehicle Routing Problem · Waste collection · Waste management · Computer Science · Engineering · Mathematics · Municipal Solid Waste Management · Optimization and Mathematical Programming · Vehicle Routing Optimization Methods

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