scholarly journals Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: A case study

2019 ◽  
Vol 37 (1_suppl) ◽  
pp. 4-13 ◽  
Author(s):  
Erfan Babaee Tirkolaee ◽  
Parvin Abbasian ◽  
Mehdi Soltani ◽  
Seyed Ali Ghaffarian
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Computational Time ◽  
Waste Collection ◽  
Urban Waste ◽  
Routing Problem ◽  
Great Performance ◽  
Hard Problems

This paper studies a multi-trip vehicle routing problem with time windows specifically related to urban waste collection. Urban waste collection is one of the municipal activities with large costs and has many practical difficulties. In other words, waste collection and disposal is a costly task due to high operating expenses (fuel, maintenance, recycling, manpower, etc.) and small improvements in this field can result in tremendous savings on municipal expenditure. In the raised problem, the goal is to minimize total cost including traversing cost, vehicle employment cost, and exit penalty from permissible time windows. In this problem, the waste is deposited at the points indicating the demand nodes, in which each demand shows the volume of generated waste. Considering multiple trips for vehicles and time windows are the most critical features of the problem, so that the priorities of serving some specific places such as hospitals can be observed. Since vehicle routing problems (VRP) belongs to NP-hard problems, an efficient simulated annealing (SA) is proposed to solve the problem. The computational results show that our proposed algorithm has a great performance in a short computational time in comparison with the CPLEX solver. Finally, in order to demonstrate the applicability of the model, a case study is analyzed in Iran, and the optimal policies are presented.

scholarly journals Solving practical waste collection with time windows in an urban area

2020 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Abdulwahab Almutairi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Optimal Solutions ◽  
Waste Collection ◽  
Routing Problem ◽  
Iterated Greedy

In logistics, several algorithms can be implemented in order to solve the problems of the vehicle routing with variants in order to find near-optimal solutions. Waste Collection can be considered as an essential logistic activity within any area or city. This kind of paper is aimed to implement Iterated greedy (IG) and Adaptive Large Neighborhood Search (ALNS) to solve waste collection vehicle routing problem with time windows on a real-case study. The idea is to generate an efficient way to collect waste problems in an area located in Riyadh, Saudi Arabia. Moreover, generating a route plays a significant role in terms of serving all customers’ demands who have own different time windows of receiving goods. Also, the performance of the proposed algorithms according to all instances is examined and minimizing the total costs and meeting all constraints that related to capacity, time windows, and others. To evaluate the execution of the presented algorithms, the computational results showed essential improvements, and also ALNS algorithm generates reasonable solutions in terms of total costs and a reasonable amount of time, when compared to other algorithms.  

scholarly journals Waste Collection Vehicle Routing Problem Model with Multiple Trips, Time Windows, Split Delivery, Heterogeneous Fleet and Intermediate Facility

2020 ◽  
Vol 24 (5) ◽  
pp. 55-64
Author(s):  
Filscha Nurprihatin ◽  
Anggun Lestari
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Computational Time ◽  
Waste Collection ◽  
Routing Problem ◽  
Problem Model ◽  
Split Delivery ◽  
Heterogeneous Fleet ◽  
Intermediate Facilities

Waste Collection Vehicle Routing Problem (WCVRP) is one of the developments of a Vehicle Routing Problem, which can solve the route determination of transporting waste. This study aims to develop a model from WCVRP by adding characteristics such as split delivery, multiple trips, time windows, heterogeneous fleet, and intermediate facilities alongside an objective function to minimize costs and travel distance. Our model determines the route for transporting waste especially in Cakung District, East Jakarta. The additional characteristics are obtained by analyzing the characteristics of waste transportation in the area. The models are tested using dummy data to analyze the required computational time and route suitability. The models contribute to determining the route of transporting waste afterward. The WCVRP model has been successfully developed, conducted the numerical testing, and implemented with the actual characteristics such as split delivery, multiple trips, time windows, heterogeneous fleets, and intermediate facilities. The output has reached the global optimal for both dummy and real data.

Grid Platform Applied to the Vehicle Routing Problem with Time Windows for the Distribution of Products

2012 ◽  
pp. 52-81
Author(s):  
Marco Antonio Cruz-Chávez ◽  
Abelardo Rodríguez-León ◽  
Rafael Rivera-López ◽  
Fredy Juárez-Pérez ◽  
Carmen Peralta-Abarca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Grid Computing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Solution Space ◽  
Routing Problem ◽  
Computing Platform ◽  
Hard Problems ◽  
Computing Platforms

Around the world there have recently been new and more powerful computing platforms created that can be used to work with computer science problems. Some of these problems that are dealt with are real problems of the industry; most are classified by complexity theory as hard problems. One such problem is the vehicle routing problem with time windows (VRPTW). The computational Grid is a platform which has recently ventured into the treatment of hard problems to find the best solution for these. This chapter presents a genetic algorithm for the vehicle routing problem with time windows. The algorithm iteratively applies a mutation operator, first of the intelligent type and second of the restricting type. The algorithm takes advantage of Grid computing to increase the exploration and exploitation of the solution space of the problem. The Grid performance is analyzed for a genetic algorithm and a measurement of the latencies that affect the algorithm is studied. The convenience of applying this new computing platform to the execution of algorithms specially designed for Grid computing is presented.

scholarly journals METAHEURISTICS FOR THE WASTE COLLECTION VEHICLE ROUTING PROBLEM IN URBAN AREAS

2020 ◽  
pp. 001
Author(s):  
Aleksandar Stanković ◽  
Danijel Marković ◽  
Goran Petrović ◽  
Žarko Čojbašić
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Urban Areas ◽  
Heuristic Algorithms ◽  
Municipal Waste ◽  
Waste Collection ◽  
Swarm Optimization ◽  
Urban Waste ◽  
Routing Problem ◽  
Capacitated Vehicle

This paper presents a methodology for solving the municipal waste collection problem in urban areas. The problem is treated as a distance-constrained capacitated vehicle routing problem for municipal waste collection (DCCVRP-MWC). To solve this problem, four meta-heuristic algorithms were used: Genetic algorithm (GA), Simulated annealing (SA), Particle swarm optimization (PSO) and Ant colony optimization (ACO). Vehicle guidance plays a huge role in large transportation companies, and with this test, we propose one of several algorithms for solving urban waste collection problems.

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