Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm
•PSO based CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in PSO based CVRP model.•Waste route is optimized based on collected waste, travel distance and tightness.•PSO based CVRP model is a valuable tool for waste collection route optimization. Waste...
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| Published in | Waste management (Elmsford) Vol. 71; pp. 31 - 41 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Ltd
01.01.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0956-053X 1879-2456 1879-2456 |
| DOI | 10.1016/j.wasman.2017.10.019 |
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| Abstract | •PSO based CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in PSO based CVRP model.•Waste route is optimized based on collected waste, travel distance and tightness.•PSO based CVRP model is a valuable tool for waste collection route optimization.
Waste 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. |
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| AbstractList | Waste 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. Waste 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.Waste 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. •PSO based CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in PSO based CVRP model.•Waste route is optimized based on collected waste, travel distance and tightness.•PSO based CVRP model is a valuable tool for waste collection route optimization. Waste 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. |
| Author | Scavino, Edgar Hussain, A. Basri, H. Akhtar, Mahmuda Begum, R.A. Hannan, M.A. |
| Author_xml | – sequence: 1 givenname: M.A. surname: Hannan fullname: Hannan, M.A. email: hannan@uniten.edu.my organization: Dept. of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia – sequence: 2 givenname: Mahmuda surname: Akhtar fullname: Akhtar, Mahmuda email: mahmuda@siswa.ukm.edu.my organization: Dept. of Civil and Structural Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia – sequence: 3 givenname: R.A. surname: Begum fullname: Begum, R.A. email: rawshan@ukm.edu.my organization: Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia – sequence: 4 givenname: H. surname: Basri fullname: Basri, H. email: drhb@ukm.edu.my organization: Dept. of Civil and Structural Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia – sequence: 5 givenname: A. surname: Hussain fullname: Hussain, A. email: draini@ukm.edu.my organization: Dept. of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia – sequence: 6 givenname: Edgar surname: Scavino fullname: Scavino, Edgar email: scavino@ukm.edu.my organization: Dept. of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29079284$$D View this record in MEDLINE/PubMed |
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| Keywords | Threshold waste level Waste collection PSO CVRP model Route optimization |
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| Snippet | •PSO based CVRP model for waste collection and route optimization.•TWL and scheduling concepts are applied in PSO based CVRP model.•Waste route is optimized... Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable... |
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| SubjectTerms | algorithms capital CVRP model data collection energy use and consumption environmental impact labor PSO Route optimization solid wastes system optimization Threshold waste level Waste collection waste management |
| Title | Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm |
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