An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives

Li, Yongbo; Soleimani, Hamed; Zohal, Mostafa

doi:10.1016/j.jclepro.2019.03.185

Cited by 222 publications

(97 citation statements)

References 48 publications

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“…The arrows in the figure indicate the direction of segmentation. The sectors within the inner circle are: [10,7,1,3], [5], [12,8], the sectors within the outer circle sectors are: [6], [2,11], [4,9,13].…”

Section: Segment the Circlementioning

confidence: 99%

“…According to the above rules, a result of the sector arrangement of the depot A is shown in Figure 4a. The sector sequence is: [12,8], [4,9,13], [10,7,1,3], [6], [2,11], [5]. The rearranged order using CWS method.…”

Section: Arrange the Sectorsmentioning

confidence: 99%

“…In Figure 6, customers 4 and 1 of route 1, customers 3 and 6 of route 2, and customers 2 and 5 of route 3 need to be paired. Consequently, the list is: [ [4,3], [4,6], [4,2], [4,5], [1,3], [1,6], [1,2], [1,5], [3,2], [3,5], [6,2], [6,5]], a total of [(3 − 1)ˆ2 + (3 − 1)] × 2 = 12 pairs.…”

Section: Pair the First And Last Customersmentioning

confidence: 99%

“…They used Cordeau's benchmark instances to evaluate results. Some articles [5][6][7] adopted ACO to solve the variants of MDVRP, such as MDVRP with multiple objectives and MDVRP with time windows.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Shi

et al. 2020

Applied Sciences

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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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Section: Segment the Circlementioning

confidence: 99%

Section: Arrange the Sectorsmentioning

confidence: 99%

Section: Pair the First And Last Customersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Shi

et al. 2020

Applied Sciences

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“…Application practice proves that the optimization effect of the Ant Week algorithm is significantly better than the other two algorithms. The reason is analyzed because the Ant Week algorithm uses global feedback information in the search process, while the ant secret and ant quantity algorithms use local feedback information [28][29][30].…”

Section: Ant Colony Optimization Algorithm Principlementioning

confidence: 99%

Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

Yang

Guo

et al. 2020

Applied Sciences

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The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

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A Two-Pheromone Trail Ant Colony System Approach for the Heterogeneous Vehicle Routing Problem with Time Windows, Multiple Products and Product Incompatibility

Palma-Blanco

González

Paternina-Arboleda

2019

Lecture Notes in Computer Science

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An improved ant colony optimization algorithm for the multi-depot green vehicle routing problem with multiple objectives

Cited by 222 publications

References 48 publications

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

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

Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

A Two-Pheromone Trail Ant Colony System Approach for the Heterogeneous Vehicle Routing Problem with Time Windows, Multiple Products and Product Incompatibility

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