Ant colony optimization techniques for the vehicle routing problem

Bell, John E.; McMullen, Patrick R.

doi:10.1016/j.aei.2004.07.001

Cited by 595 publications

(251 citation statements)

References 18 publications

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“…The ant colony algorithm is a metaheuristic algorithm, which was used to solve the VRP. Bell and McMullen [35] compared the ant colony algorithm with the TS search algorithm and genetic algorithm and found that the ant colony algorithm required less computation time [35]. Gribkovskaia et al [36] proposed a mixed integer programming model (SVRPPD), which was compared with the classical algorithm and the improved heuristic algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

Zhang

Shi

Chen

et al. 2017

Journal of Advanced Transportation

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The application of automated vehicles in logistics can efficiently reduce the cost of logistics and reduce the potential risks in the last mile. Considering the path restriction in the initial stage of the application of automated vehicles in logistics, the conventional model for a vehicle routing problem (VRP) is modified. Thus, the automated vehicle routing problem with time windows (AVRPTW) model considering path interruption is established. Additionally, an improved particle swarm optimisation (PSO) algorithm is designed to solve this problem. Finally, a case study is undertaken to test the validity of the model and the algorithm. Four automated vehicles are designated to execute all delivery tasks required by 25 stores. Capacities of all of the automated vehicles are almost fully utilised. It is of considerable significance for the promotion of automated vehicles in last-mile situations to develop such research into real problems arising in the initial period.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

Zhang

Shi

Chen

et al. 2017

Journal of Advanced Transportation

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“…The utilize of AC become first functional to the traveling salesman issues and the quadratic assignment issue and has for the reason that been implemented to other issue that comprises the machine tool problematic and the multiple objective space planning problematic and JIT sequencing problematic [6]. …”

Section: Fig 3 Aco Techniquementioning

confidence: 99%

“…However, the continued random selection of paths thru way of individual ants facilitates the colony find out alternate routes and insures successful navigation around obstacles that interrupt a route. Trail selection by way of ants is a pseudo-random proportional manner and is a key element of the simulation set of rules of ACO [6].…”

Section: Fig 3 Aco Techniquementioning

confidence: 99%

A Survey of Various Optimization Techniques in Data Mining

Anjana¹,

Upadhyay²

2017

International Advanced Research Journal in Science, Engineering

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With the advancement in the amount of data generation, a procedure of taking out of useful information and patterns from huge data become crucial which is termed as Data Mining. It is also called as knowledge discovery process, knowledge mining from data, knowledge extraction or data /pattern analysis. In this paper, we discussed about a few optimization techniques which are quite useful for the extraction of optimal results. Animal migration optimization is the process which considers the behavior of the animal movement for moving to other positions. Genetic Algorithm (GA) performs three operations like selection, crossover and mutation over the chromosomes for the best possible result. Ant colony optimization (ACO) is based on the action performed by ants for getting the food from the shortest and superior path. And finally particle swarm optimization (PSO) which considers the particles movement and velocity then calculate best position for the movement. This paper would be useful for the best understanding of optimization technique.

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“…The direction is then determined according to the obtained results. ACO has been used in following areas before: various subfields of data mining [16], real world problems [17], mathematical modeling [18], network routing problems [19], prediction of energy consumption [20], and software testing [21].…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

A bat-inspired algorithm for prioritizing test cases

Öztürk

2017

Vietnam J Comput Sci

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By ordering test cases, early fault detection is focused on test case prioritization. In this field, it is widely known that algorithm and coverage criteria focused works are common. Previous works, which are related to test case prioritization, showed that practitioners need a novel method that optimizes test cases according to the cost of each test case instead of regarding the total cost of a test suite. In this work, by utilizing local and global search properties of a bat algorithm, a new bat-inspired test cases prioritization algorithm (BITCP) is proposed. In order to develop BITCP, test case execution time and the number of faults were adapted to the distance from the prey and loudness, respectively. The proposed method is then compared with four methods which are commonly used in this field. According to the results of the experiment, BITCP is superior to the conventional methods. In addition, as the complexity of the code of test cases increases, the decline in average percentage of fault detection is less in BITCP than the other four comparison algorithms produced.

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Ant colony optimization techniques for the vehicle routing problem

Cited by 595 publications

References 18 publications

Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

Analysis of an Automated Vehicle Routing Problem in Logistics considering Path Interruption

A Survey of Various Optimization Techniques in Data Mining

A bat-inspired algorithm for prioritizing test cases

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