The Performance of Ant System in Solving Multi Traveling Salesmen Problem

Kencana, I Putu Eka Nila; Harini, Luh Putu Ida; Mayuliana, K.

doi:10.1016/j.procs.2017.12.128

Cited by 14 publications

(7 citation statements)

References 7 publications

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“…The Multiple Traveling Salesmen Problem is considered to be a special case of the classical Traveling Salesman Problem. According to the classification of the Traveling Salesman Problem as an NP-hard problem, the Multiple Traveling Salesmen Problem is more difficult than the classical variant [27][28][29]. The Traveling Salesman Problem is a typical combinatorial optimization problem [30] and is generally defined such that a salesman m = 1 starts his travel from a starting node and returns after visiting n nodes, so that every node is visited only once.…”

Section: Multiple Traveling Salesmen Problemmentioning

confidence: 99%

Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms

Mokhi

Addaim

2020

Sustainability

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Wind energy is currently one of the fastest-growing renewable energy sources in the world. For this reason, research on methods to render wind farms more energy efficient is reasonable. The optimization of wind turbine positions within wind farms makes the exploitation of wind energy more efficient and the wind farms more competitive with other energy resources. The investment costs alone for substation and electrical infrastructure for offshore wind farms run around 15–30% of the total investment costs of the project, which are considered high. Optimizing the substation location can reduce these costs, which also minimizes the overall cable length within the wind farm. In parallel, optimizing the cable routing can provide an additional benefit by finding the optimal grid network routing. In this article, the authors show the procedure on how to create an optimized wind farm already in the design phase using metaheuristic algorithms. Besides the optimization of wind turbine positions for more energy efficiency, the optimization methods of the substation location and the cable routing for the collector system to avoid cable losses are also presented.

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Section: Multiple Traveling Salesmen Problemmentioning

confidence: 99%

Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms

Mokhi

Addaim

2020

Sustainability

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“…One of these algorithms is the ACO, which is also frequently used to solve TSP efficiently. In the study by Kencana et al used Ant System to solve MTSP and stated that the increase in salesperson had a significant effect on working time but not a significant effect on minimum total distance [3]. As another example, Pan Junjie et al also tried to solve MTSP with ACO algorithm by using some standard data sets from TSPLIB.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…Point 0 represents one depot of paths using the "byg29" dataset. The chromosome sequence of a successful solution after acceptable iteration = [0, 1,28,2,25,4,8,11,5,20,9,19,3,14,17,16,21,13,10,18,23,12,27,7,26,22,6,24,15,9,19]. The path plot of this chromosome is shown in Figure 7.…”

Section: Figure 5 Solution Costs Based On Generationmentioning

confidence: 99%

An Evolutionary Approach to Multiple Traveling Salesman Problem for Efficient Distribution of Pharmaceutical Products

Kocyigit

Şahingöz

Di̇ri̇

2020

2020 International Conference on Electrical Engineering (ICEE)

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Considerable growth of computer science has created novel solutions for variable problem fields and has increased the efficiency of available solutions. Evolutionary algorithms are quite successful in dealing with real-world problems that require optimization. In this article, we implemented a Genetic Algorithm that is well known evolutionary algorithm in order to provide an efficient solution for the Distribution of Pharmaceutical Products, which is a vital optimization problem, especially in situations such as a pandemic. The Multiple Traveling Salesman Problem approach was used to distribute pharmaceutical products as soon as possible. Moreover, we strengthened our proposal algorithm with 2-Opt Algorithm to get optimal results in earlier iterations. Different datasets from a library were applied to measure the quality of solutions and computation time. At the end of the work, we observed that our proposed algorithm generates successful solutions in an acceptable running time. This study will be extended with a new mutation concept as future work.

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“…e nd iter_max iter (10) where t start is the initial temperature; t end is the final temperature; iter is the current iteration; and iter_max is the maximum number of iterations specified beforehand.…”

Section: Proposed Algorithmmentioning

confidence: 99%

Modified Ant Colony Optimization Algorithm for Multiple-vehicle Traveling Salesman Problems

Oonsrikaw¹,

Thammano²

2018

IJNDC

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In this work, we extended the original Traveling Salesman Problem (TSP) to cover not only the case of multiple vehicles but also to constrain the minimum and maximum numbers of cities each vehicle can visit. Our algorithm is a modified Ant Colony Optimization (ACO) algorithm which has the ability to avoid local optima; our algorithm can be applied to transportation problem that covers either a single vehicle or multiple vehicles. To the original ACO, we added a new reproduction method, a new pheromone updating strategy, and four improved local search strategies. We tested our algorithm on several standard datasets in the TSP library. Its single-vehicle performance was compared to that of ant system (AS) and elitist ant system (EAS) algorithms. Its multiple-vehicle performance was evaluated against that of ant colony system variants reported in the literature. The experiments show that our proposed ACO's single-vehicle performance was superior to that of AS and EAS on every tested dataset and its multiple-vehicle performance was excellent.

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The Performance of Ant System in Solving Multi Traveling Salesmen Problem

Cited by 14 publications

References 7 publications

Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms

Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms

An Evolutionary Approach to Multiple Traveling Salesman Problem for Efficient Distribution of Pharmaceutical Products

Modified Ant Colony Optimization Algorithm for Multiple-vehicle Traveling Salesman Problems

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