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

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.

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

2020 ◽  
Vol 17 (2) ◽  
pp. 458 ◽  
Author(s):  
Hailin Wu ◽  
Fengming Tao ◽  
Qingqing Qiao ◽  
Mengjun Zhang
Keyword(s):  
Waste Management ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimal Solution ◽  
Point Of View ◽  
Chance Constrained Programming ◽  
Low Carbon ◽  
Waste Collection ◽  
Routing Problem ◽  
The Government

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.

scholarly journals Optimization of Vehicle Routing for Waste Collection and Transportation

2020 ◽  
Vol 17 (14) ◽  
pp. 4963 ◽  
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.

scholarly journals Tabu search algorithm for solving waste collection vehicle routing problem

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
Siti Asnor Faraien Hassan ◽  
Syarifah Zyurina Nordin
Keyword(s):  
Tabu Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Waste Collection ◽  
Routing Problem ◽  
Number Of Customers

This study considers a Waste Collection Vehicle Routing Problem where the situation happens when vehicle must make a complete trip to make disposal operation per day. The Waste Collection Vehicle Routing Problem objective is to decide the best solution where a vehicle should make the collection first between the customers since there exist larger number of customers. The method proposed to solve the Waste Collection Vehicle Routing Problem is by using Tabu Search Algorithm.

scholarly journals A REVIEW OF DISRUPTION MANAGEMENT IN VEHICLE ROUTING PROBLEM (VRP), TRANSPORT DESIGN AND SCHEDULING

2021 ◽  
Vol 7 (7) ◽  
pp. 442-453
Author(s):  
James Kwabena Odum ◽  
◽  
Rev Fr. Dr. Augustine Owusu-Addo ◽  
Nana Kyere-Sacrifice ◽  
Addai-Amoah Anthony Kwarteng ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Clustering Analysis ◽  
Solution Method ◽  
Disruption Management ◽  
Arc Routing ◽  
Waste Collection ◽  
Routing Problem ◽  
Disposal Facility ◽  
Node Routing

In the case of an unexpected occurrence, disruption management is a method of rescheduling activities and it has been used in a variety of fields, including organized carrier scheduling and project management. The purpose of this review is to examine Ant Colony Optimization (ACO), the problems of Heuristics for Delivery Waste Collection (VRP), ARC Routing, Node Routing, and Container/skip. Other issues and problems examined in the paper were Non-Skip, Algorithms for the VRP, Improvement Algorithms, Simulated Annealing, and ACO for Capacitated Vehicle Routing, Clustering Analysis, and Probabilistic-D Cluster Analysis. It covers the fundamental characteristics of disruption management as well as the related goals and kinds of disruption that may occur in this setting. The various formulations and solution techniques are discussed in facets. A collection of relevant articles has been summarized and categorized according to the kind of disruption problem being addressed, the relevant goals, and the solution method used to resolve the problem. Vehicles must be emptied at a trash disposal facility before they may be used to collect garbage from further clients. The growing amount of solid waste generated as a result of p

scholarly journals A Modified Harmony Search Algorithm for Solving the Dynamic Vehicle Routing Problem with Time Windows

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shifeng Chen ◽  
Rong Chen ◽  
Jian Gao
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.

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