Iterated greedy with variable neighborhood search for a multiobjective waste collection problem

2020 ◽  
Vol 145 ◽  
pp. 113101 ◽  
Author(s):  
Laura Delgado-Antequera ◽  
Rafael Caballero ◽  
Jesús Sánchez-Oro ◽  
J Manuel Colmenar ◽  
Rafael Martí
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Waste Collection ◽  
Iterated Greedy

scholarly journals Modeling the Municipal Waste Collection Using Genetic Algorithms

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 513
Author(s):  
Elisabete Alberdi ◽  
Leire Urrutia ◽  
Aitor Goti ◽  
Aitor Oyarbide-Zubillaga
Keyword(s):  
Genetic Algorithm ◽  
Variable Neighborhood Search ◽  
Real Data ◽  
Municipal Waste ◽  
Neighborhood Search ◽  
Initial Population ◽  
Waste Collection ◽  
Reduction Of Emissions ◽  
Apparent Reasons ◽  
Unsolved Issue

Calculating adequate vehicle routes for collecting municipal waste is still an unsolved issue, even though many solutions for this process can be found in the literature. A gap still exists between academics and practitioners in the field. One of the apparent reasons why this rift exists is that academic tools often are not easy to handle and maintain by actual users. In this work, the problem of municipal waste collection is modeled using a simple but efficient and especially easy to maintain solution. Real data have been used, and it has been solved using a Genetic Algorithm (GA). Computations have been done in two different ways: using a complete random initial population, and including a seed in this initial population. In order to guarantee that the solution is efficient, the performance of the genetic algorithm has been compared with another well-performing algorithm, the Variable Neighborhood Search (VNS). Three problems of different sizes have been solved and, in all cases, a significant improvement has been obtained. A total reduction of 40% of itineraries is attained with the subsequent reduction of emissions and costs.

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.  

An Effective Variable Neighborhood Search with Perturbation for Location-Routing Problem

2019 ◽  
Vol 28 (07) ◽  
pp. 1950024
Author(s):  
Hua Jiang ◽  
Corinne Lucet ◽  
Laure Devendeville ◽  
Chu-Min Li
Keyword(s):  
Facility Location ◽  
Vehicle Routing ◽  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Challenging Problem ◽  
Waste Collection ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Practical Applications ◽  
Location Routing

Location-Routing Problem (LRP) is a challenging problem in logistics, which combines two types of decision: facility location and vehicle routing. In this paper, we focus on LRP with multiple capacitated depots and one uncapacitated vehicle per depot, which has practical applications such as mail delivery and waste collection. We propose a simple iterated variable neighborhood search with an effective perturbation strategy to solve the LRP variant. The experiments show that the algorithm is efficient and can compute better solutions than previous algorithms on tested instances.

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