Feasible Initial Population with Genetic Diversity for a Population-Based Algorithm Applied to the Vehicle Routing Problem with Time Windows

Cruz-Chávez, Marco Antonio; Martinez-Oropeza, Alina

doi:10.1155/2016/3851520

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…It can be applied as a criterion for achieving a specified diversity of the initial population, as well. For example, new solutions can be created until the entropy exceeds a specific limit, which allows improving the convergence to the optimal solution [ 39 , 40 ].…”

Section: Heterogeneitymentioning

confidence: 99%

A Self-Adaptive Discrete PSO Algorithm with Heterogeneous Parameter Values for Dynamic TSP

Strąk

Skinderowicz

Boryczka

et al. 2019

Entropy

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This paper presents a discrete particle swarm optimization (DPSO) algorithm with heterogeneous (non-uniform) parameter values for solving the dynamic traveling salesman problem (DTSP). The DTSP can be modeled as a sequence of static sub-problems, each of which is an instance of the TSP. In the proposed DPSO algorithm, the information gathered while solving a sub-problem is retained in the form of a pheromone matrix and used by the algorithm while solving the next sub-problem. We present a method for automatically setting the values of the key DPSO parameters (except for the parameters directly related to the computation time and size of a problem).We show that the diversity of parameters values has a positive effect on the quality of the generated results. Furthermore, the population in the proposed algorithm has a higher level of entropy. We compare the performance of the proposed heterogeneous DPSO with two ant colony optimization (ACO) algorithms. The proposed algorithm outperforms the base DPSO and is competitive with the ACO.

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Section: Heterogeneitymentioning

confidence: 99%

A Self-Adaptive Discrete PSO Algorithm with Heterogeneous Parameter Values for Dynamic TSP

Strąk

Skinderowicz

Boryczka

et al. 2019

Entropy

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show abstract

“…Constraints (2) and (3) guarantee that each customer is served by exactly one vehicle. Vehicle capacity constraint is found in (4). Finally, constraints (5) and (6) check vehicle availability.…”

Section: Dynamic Multidepot Vehiclementioning

confidence: 99%

“…By transforming the TSP, a great number of different kinds of VRP are designed. Generally, VRP has been classified to the following several variants: Capacitated VRP (CVRP), VRP with time windows (VRPTW), VRP with Pickup and Delivery (VRPPD), multidepot VRP (MDVRP), and so on [2][3][4][5][6]. Most particularly, considering that many logistics companies are desirous to improve service quality and save time, the MDVRP receives more and more attentions.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Ant Colony Optimization for Dynamic Multidepot Vehicle Routing Problem

Duan

2018

Discrete Dynamics in Nature and Society

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In the real world, the vehicle routing problem (VRP) is dynamic and variable, so dynamic vehicle routing problem (DVRP) has obtained more and more attentions among researchers. Meanwhile, due to actual constraints of service hours and service distances, logistics companies usually build multiple depots to serve a great number of dispersed customers. Thus, the research of dynamic multidepot vehicle routing problem (DMDVRP) is significant and essential. However, it has not attracted much attention. In this paper, firstly, a clustering approach based on the nearest distance is proposed to allocate all customers to the depots. Then a hybrid ant colony optimization (HACO) with mutation operation and local interchange is introduced to optimize vehicle routes. In addition, in order to deal with dynamic problem of DMDVRP quickly, a real-time addition and optimization approach is designed to handle the new customer requests. Finally, the t-test is applied to evaluate the proposed algorithm; meanwhile the relations between degrees of dynamism (dod) and HACO are discussed minutely. Experimental results show that the HACO algorithm is feasible and efficient to solve DMDVRP.

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“…In addition, due to the limits of the vehicle running length and/or travelling time, service process may need multiple different routes [6,7]. Actually, the VRP has been classified to several variants, such as Capacitated VRP (CVRP), Multidepot VRP (MDVRP), and VRP with time windows (VRPTW) [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization

Duan

2018

Discrete Dynamics in Nature and Society

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As we all know, there are a great number of optimization problems in the world. One of the relatively complicated and highlevel problems is the vehicle routing problem (VRP). Dynamic vehicle routing problem (DVRP) is a major variant of VRP, and it is closer to real logistic scene. In DVRP, the customers' demands appear with time, and the unserved customers' points must be updated and rearranged while carrying out the programming paths. Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades. In this paper, we have two main contributions to solving DVRP. Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO), which is the traditional Ant Colony Optimization (ACO) fusing improved K-means and crossover operation. K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely. Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method. In the experiment, the results for different scale problems are compared to those of previously published papers. Experimental results show that the algorithm is feasible and efficient.

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Feasible Initial Population with Genetic Diversity for a Population-Based Algorithm Applied to the Vehicle Routing Problem with Time Windows

Cited by 5 publications

References 17 publications

A Self-Adaptive Discrete PSO Algorithm with Heterogeneous Parameter Values for Dynamic TSP

A Self-Adaptive Discrete PSO Algorithm with Heterogeneous Parameter Values for Dynamic TSP

A Hybrid Ant Colony Optimization for Dynamic Multidepot Vehicle Routing Problem

Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization

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