Optimizing garbage collection vehicle routing problem with alternative fuel-powered vehicles

Gajpal, Yuvraj; Abdulkader, M.M.S.; Zhang, Shuai; Appadoo, S. S.

doi:10.1080/02331934.2017.1349126

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…The obtained results from this study are compared with those published by Gajpal et al (2017) who studied the MCGVRP in the collection process of residential garbage. The trend of the results is similar in terms of the effectiveness of multi-compartment in vehicle routing problem (VRP).…”

Section: Resultsmentioning

confidence: 93%

“…For a fair comparison, we let Q = Q1 + Q2 and Q1 = Q2. Under the single-compartment EVs problem, the problem is decomposed into two subproblems (Gajpal et al, 2017). The first subproblem collects type 1 garbage and the second sub problem collects type 2 garbage.…”

Section: Resultsmentioning

confidence: 99%

“…This data set is adapted for constructing an instance for the CCMCEVRP, and we consider three different sizes of problems: two small sizes as P-n21-k2 and A-n32-k5; three medium sizes as P-n45-k5, P-n55-k7 and A-n62-k8; three large sizes as P-n76-k4, A-n80-k10 and P-n101-k4. Note that the spatial distance of nodes of data set A is farther than that of data set P. There is only one type of waste in this data set and this parameter is changed according to the kinds of waste in our model, according to the former research works (Gajpal et al, 2017) and (Abdulkader et al, 2015). We use the capacity ratio to measure the capacity of two compartments of the EVs.…”

Section: Model and Methodsmentioning

confidence: 99%

“…Also, waste types at smart waste bins of each node are set a ratio as well, that is, a ratio of 2:3 means the quantity of first garbage is 0.4 q i and the other one is 0.6 q i . In the meantime, to make the data meaningful for the capacity limit of CCMCEVRP, the capacity of EVs is twice as the original one (Gajpal et al, 2017). However, since the EVRP instances are not available in the current literature, the recharging stations of all instances are situated randomly based on the literature Zhang et al (2018).…”

Section: Model and Methodsmentioning

confidence: 99%

“…They limited the tour duration and minimised the sum of transportation costs, rent costs and service costs for loading and unloading. Gajpal et al (2017) formulised the Multi-Compartment Green Vehicle Routing Problem (MCGVRP), and compared the performance of Saving Algorithm (SA) and ACS algorithm in solving MCGVRP, and they also considered alternative fuel-powered vehicles with limited fuel tank capacity, thus resulting in distance-constrained tours.…”

Section: Literature Reviewmentioning

confidence: 99%

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Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins

Yang

Tao

Zhong³

2022

Waste Manag Res

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The municipal solid waste (MSW) collection and transportation issue has been studied by numerous researchers; however, a few studies consider the chance-constrained programming for co-collection of sorted waste with electric vehicles (EVs). Therefore, this article attempts to study on the chance-constrained collection and transportation problem for sorted waste with multiple separated compartments EVs. Considering the uncertainty of the waste generation rate under the scenario of application of smart waste bins, chance-constrained programming is applied to transform the uncertain model into a certain one. A Chance-Constrained Multi-Compartment Electric Vehicle Routing Problem (CCMCEVRP) is introduced and the corresponding mathematical formulation is established. A diversity-enhanced particle swarm optimisation with neighbourhood search and simulated annealing (DNSPSOSA) is proposed to solve this problem, and effectiveness of the proposed algorithms is verified by extensive numerical experiments on the newly generated instances. In addition, the application of the model is tested by comparing different compartment and different type vehicles. It is found that, compared with fuel vehicles, 32.66% of the average cost could be saved with EVs. Furthermore, the rate of cost-saving of EVs increases with the increase in the number of compartments: the improvement rate of cost-saving of two-compartment EVs and three-compartment EVs is 52.77% and 68.13%, respectively.

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Section: Resultsmentioning

confidence: 93%

Section: Resultsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Model and Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins

Yang

Tao

Zhong³

2022

Waste Manag Res

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Waste collection routing: a survey on problems and methods

Hess,

Dragomir,

Doerner

et al. 2023

Cent Eur J Oper Res

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Waste collection is a vital service performed all over the world, which heavily relies on vehicle routing. Due to regulations and local conditions, the problems and their characteristics often differ greatly. This literature survey aims to review the current state of the art overlap in waste collection and vehicle routing literature. The most notable papers are categorized according to their underlying problem type, examined and brought into relation based on their common problem characteristics. The problem types comprise general, node and arc routing problems, with vehicle routing problems being the most common, followed by arc and location routing problems. Besides the use of intermediate facilities, which is naturally very common in waste collection literature, the authors point out other interesting characteristics found in the literature and in practical problems, such as uncertain demand, personnel planning aspects, alternative collection systems or vehicle types, and characteristics related to risk or sustainability. Additionally, the authors highlight prominent scopes and objectives as well as recent developments in this area. Overall, this survey provides a selective overview and calls attention to research gaps and possible future research directions.

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On a model-free meta-heuristic approach for unconstrained optimization

Xia,

2024

J Supercomput

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Optimizing garbage collection vehicle routing problem with alternative fuel-powered vehicles

Cited by 11 publications

References 22 publications

Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins

Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins

Waste collection routing: a survey on problems and methods

On a model-free meta-heuristic approach for unconstrained optimization

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