Publication:
Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm

dc.citedby128
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorAkhtar M.en_US
dc.contributor.authorBegum R.A.en_US
dc.contributor.authorBasri H.en_US
dc.contributor.authorHussain A.en_US
dc.contributor.authorScavino E.en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid56781056700en_US
dc.contributor.authorid14007780000en_US
dc.contributor.authorid57192888245en_US
dc.contributor.authorid57208481391en_US
dc.contributor.authorid23467686400en_US
dc.date.accessioned2023-05-29T06:57:16Z
dc.date.available2023-05-29T06:57:16Z
dc.date.issued2018
dc.descriptionCosts; Efficiency; Routing algorithms; Scheduling; Solid wastes; Vehicle routing; Capacitated vehicle routing problem; Modified particle swarm optimization; Optimized models; Route optimization; Solid waste collection; Threshold waste level; Travel distance; Waste collection; Particle swarm optimization (PSO); fuel; algorithm; numerical model; optimization; routing; solid waste; transport vehicle; waste disposal; algorithm; Article; capacitated vehicle routing problem model; controlled study; cost; decision making; environmental impact; motor vehicle; nonbiological model; particle swarm optimization algorithm; priority journal; problem solving; process optimization; socioeconomics; solid waste management; travel; validation process; economics; solid waste; waste management; Algorithms; Costs and Cost Analysis; Solid Waste; Waste Managementen_US
dc.description.abstractWaste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70�75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. � 2017 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.wasman.2017.10.019
dc.identifier.epage41
dc.identifier.scopus2-s2.0-85032214632
dc.identifier.spage31
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85032214632&doi=10.1016%2fj.wasman.2017.10.019&partnerID=40&md5=57cfa23ac17e98d6b0dd2d84475ff3e4
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24232
dc.identifier.volume71
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleWaste Management
dc.titleCapacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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