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

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.

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Optimization of Vehicle Routing for Waste Collection and Transportation

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17144963 ◽

2020 ◽

Vol 17 (14) ◽

pp. 4963 ◽

Cited By ~ 2

Author(s):

Hailin Wu ◽

Fengming Tao ◽

Bo Yang

Keyword(s):

Waste Management ◽

Local Search ◽

Environmental Protection ◽

Vehicle Routing ◽

Vehicle Routing Problem ◽

High Efficiency ◽

Optimal Solution ◽

Waste Collection ◽

Negative Effects ◽

Routing Problem

For the sake of solving the optimization problem of urban waste collection and transportation in China, a priority considered green vehicle routing problem (PCGVRP) model in a waste management system is constructed in this paper, and specific algorithms are designed to solve the model. We pay particular concern to the possibility of immediate waste collection services for high-priority waste bins, e.g., those containing hospital or medical waste, because the harmful waste needs to be collected immediately. Otherwise, these may cause dangerous or negative effects. From the perspective of environmental protection, the proposed PCGVRP model considers both greenhouse gas (GHG) emission costs and conventional waste management costs. Waste filling level (WFL) is considered with the deployment of sensors on waste bins to realize dynamic routes instead of fixed routes, so that the economy and efficiency of waste collection and transportation can be improved. The optimal solution is obtained by a local search hybrid algorithm (LSHA), that is, the initial optimal solution is obtained by particle swarm optimization (PSO) and then a local search is performed on the initial optimal solution, which will be optimized by a simulated annealing (SA) algorithm by virtue of the global search capability. Several instances are selected from the database of capacitated vehicle routing problem (CVRP) so as to test and verify the effectiveness of the proposed LSHA algorithm. In addition, to obtain credible results and conclusions, a case using data about waste collection and transportation is employed to verify the PCGVRP model, and the effectiveness and practicability of the model was tested by setting a series of values of bins’ number with high priority and WFLs. The results show that (1) the proposed model can achieve a 42.3% reduction of negative effect compared with the traditional one; (2) a certain value of WFL between 60% and 80% can realize high efficiency of the waste collection and transportation; and (3) the best specific value of WFL is determined by the number of waste bins with high priority. Finally, some constructive propositions are put forward for the Environmental Protection Administration and waste management institutions based on these conclusions.

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A Heuristic Solution Method for Multi-Depot Vehicle Routing-Based Waste Collection Problems

Applied Sciences ◽

10.3390/app10072403 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2403

Author(s):

Yanjun Shi ◽

Lingling Lv ◽

Fanyi Hu ◽

Qiaomei Han

Keyword(s):

Vehicle Routing ◽

Waste Disposal ◽

Vehicle Routing Problem ◽

Solution Method ◽

Search Algorithm ◽

Optimal Solution ◽

Waste Collection ◽

Heuristic Solution ◽

Routing Problem ◽

Combination Optimization

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm.

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A search space analysis for the waste collection vehicle routing problem with time windows

Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09 ◽

10.1145/1569901.1570175 ◽

2009 ◽

Cited By ~ 5

Author(s):

Andrew Runka ◽

Beatrice Ombuki-Berman ◽

Mario Ventresca

Keyword(s):

Vehicle Routing ◽

Vehicle Routing Problem ◽

Time Windows ◽

Search Space ◽

Waste Collection ◽

Routing Problem ◽

Space Analysis ◽

Search Space Analysis

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Solving vehicle routing problem by using improved genetic algorithm for optimal solution

Journal of Computational Science ◽

10.1016/j.jocs.2017.04.003 ◽

2017 ◽

Vol 21 ◽

pp. 255-262 ◽

Cited By ~ 57

Author(s):

Mazin Abed Mohammed ◽

Mohd Khanapi Abd Ghani ◽

Raed Ibraheem Hamed ◽

Salama A. Mostafa ◽

Mohd Sharifuddin Ahmad ◽

...

Keyword(s):

Genetic Algorithm ◽

Vehicle Routing ◽

Vehicle Routing Problem ◽

Optimal Solution ◽

Improved Genetic Algorithm ◽

Routing Problem

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Meta-heuristic Approach to Solve Mixed Vehicle Routing Problem with Backhauls in Enterprise Information System of Service Industry

Enterprise Information Systems and Implementing IT Infrastructures ◽

10.4018/978-1-61520-625-4.ch015 ◽

2010 ◽

pp. 210-225

Author(s):

S. P. Anbuudayasankar ◽

K. Ganesh ◽

Tzong-Ru Lee

Keyword(s):

Vehicle Routing ◽

Enterprise Resource Planning ◽

Vehicle Routing Problem ◽

Service Industry ◽

Optimal Solution ◽

Resource Planning ◽

Enterprise Information ◽

Solution Quality ◽

Routing Problem ◽

Support Tool

This chapter presents the development of simulated annealing (SA) for a health care application which is modeled as Single Depot Vehicle routing problem called Mixed Vehicle Routing Problem with Backhauls (MVRPB), an extension of Vehicle Routing Problem with Backhauls (VRPB). This variant involves both delivery and pick-up customers and sequence of visiting the customers is mixed. The entire pick-up load should be taken back to depot. The latest rapid advancement of meta-heuristics has shown that it can be applied in practice if they are personified in packaged information technology (IT) solutions along with the combination of a Supply Chain Management (SCM) application integrated with an enterprise resource planning (ERP) resulted to this decision support tool. This chapter provides empirical proof in sustain of the hypothesis, that a population extension of SA with supportive transitions leads to a major increase of efficiency and solution quality for MVRPB if and only if the globally optimal solution is located close to the center of all local optimal solutions.

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Optimization of the simultaneous pickup and delivery vehicle routing problem based on carbon tax

Industrial Management & Data Systems ◽

10.1108/imds-02-2019-0102 ◽

2019 ◽

Vol 119 (9) ◽

pp. 2055-2071 ◽

Cited By ~ 3

Author(s):

Gaoyuan Qin ◽

Fengming Tao ◽

Lixia Li ◽

Zhenyu Chen

Keyword(s):

Vehicle Routing ◽

Vehicle Routing Problem ◽

Carbon Tax ◽

Pickup And Delivery ◽

Vehicle Speed ◽

Low Carbon ◽

Delivery Vehicle ◽

Routing Problem ◽

Content Type ◽

Simultaneous Pickup And Delivery

Purpose In order to reduce logistics transportation costs and respond to low-carbon economy, the purpose of this paper is to study the more practical and common simultaneous pickup and delivery vehicle routing problem, which considers the carbon tax policy. A low-carbon simultaneous pickup and delivery vehicle routing problem model is constructed with the minimum total costs as the objective function. Design/methodology/approach This study develops a mathematical optimization model with the minimum total costs, including the carbon emissions costs as the objective function. An adaptive genetic hill-climbing algorithm is designed to solve the model. Findings First, the effectiveness of the algorithm is verified by numerical experiments. Second, the research results prove that carbon tax mechanism can effectively reduce carbon emissions within effective carbon tax interval. Finally, the research results also show that, under the carbon tax mechanism, the effect of vehicle speed on total costs will become more obvious with the increase of carbon tax. Research limitations/implications This paper only considers the weight of the cargo, but it does not consider the volume of the cargo. Originality/value Few studies focus on environmental issues in the simultaneous pickup and delivery problem. Thus, this paper constructs a green path optimization model, combining the carbon tax mechanism for the problem. This paper further analyzes the impact of carbon tax value on total costs and carbon emission; at the same time, the effect of vehicle speed on total cost is also analyzed.

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