Metaheuristics for the tabu clustered traveling salesman problem

Zhang, Tianjiao; Ke, Liangjun; Li, Jing; Li, Jisheng; Huang, Jingqi; Li, Zexi

doi:10.1016/j.cor.2017.07.008

Cited by 23 publications

(5 citation statements)

References 21 publications

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“…Applications of this problem cover a wide range of areas. Several algorithms have been developed for solving the CTSP: approximation algorithms [25,26] , tabu search [27], Lagrangian relaxation [28]; genetic algorithms, [29], Grasp, [30]; hybrid heuristics [31]; memetic algorithms, [32]; and other heuristics [33]. A special case of the CTSP is the Ordered Clustered Traveling Salesman Problem (OCTSP), where a visit sequence to the clusters is defined a priori, [34,35].…”

Section: Literature Reviewmentioning

confidence: 99%

The Generalized Median Tour Problem: Modeling, Solving and an Application

et al. 2020

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We introduce, formulate, and solve the Generalized Median Tour Problem, which is motivated in the health supplies distribution for urban and rural areas. A region comprises districts that must be served by a specialized vehicle visiting its health facilities. We propose a distribution strategy to serve these health facilities efficiently. A single tour is determined that visits a set of health facilities (nodes) composed of disjoint clusters. The tour must visit at least one facility within each cluster, and the unvisited facilities are assigned to the closest facility on the tour. We minimize the sum of the total tour distance and the access distance traveled by the unvisited facilities. Efficient formulations are proposed and several solution strategies are developed to avoid subtours based on branch & cut. We solve a set of test instances and a real-world instance to show the efficiency of our solution approaches.

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Section: Literature Reviewmentioning

confidence: 99%

The Generalized Median Tour Problem: Modeling, Solving and an Application

et al. 2020

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“…It includes electrical design, basic design, path selection, insulation coordination design, grounding design, and various types of tower designs. In all tasks, the focus is to select the cable path, because the subsequent design work is directly affected by the path selection, which in turn has an important impact on the input cost and overall effectiveness [18]. The route of the transmission cable is selected to find the best route that meets the requirements of cost-effectiveness, convenient construction, stable operation, and compliance with national policies [19].…”

Section: Introductionmentioning

confidence: 99%

Transmission Line Planning Based on Artificial Intelligence in Smart Cities

Yang¹,

He²,

Du³

et al. 2022

Mobile Information Systems

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With the development of smart cities, it is particularly important to realize scientific and reasonable planning of transmission lines as the backbone of the power transmission system. Through the geographic information system (GIS) platform, this paper obtains the geographic information of the planning area. Then, through the typical design cost of the 110 kV transmission line subvolume of the typical cost of the power transmission and transformation project of the State Grid Corporation and the local documents of the smart city planning area, this paper obtains the estimated cost of each grid after gridding in the smart city area. After that, the research uses the ant colony algorithm to search for the optimal transmission line route in the smart city. Finally, the achievements of primary economic and technical indexes are evaluated in transmission line planning of smart city.

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“…More recently, Zhang et al (2013) introduced a new variant of CTSP called tabu CTSP (TCTSP). Vertices in TCTSP are now divided into two types of subsets: clusters and tabu vertex sets; exactly one vertex in each tabu vertex set has to be visited and the vertices within the same cluster are visited consecutively.…”

Section: Introductionmentioning

confidence: 99%

Solving the clustered traveling salesman problem with ‐relaxed priority rule

Hà

Phuong

Nhat

et al. 2020

Int Trans Operational Res

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The clustered traveling salesman problem with a prespecified order on the clusters, a variant of the wellknown traveling salesman problem, is studied in the literature. In this problem, delivery locations are divided into clusters with different urgency levels and more urgent locations must be visited before less urgent ones. However, this could lead to an inefficient route in terms of traveling cost. This priority-oriented constraint can be relaxed by a rule called d-relaxed priority that provides a trade-off between transportation cost and emergency level. Given a positive integer d, at any point along the route, the d-relaxed rule allows the vehicle to visit locations with priority p, p + 1, . . . , p + d before visiting all locations in class p, where p is the highest priority class among all unvisited locations. Our research proposes two approaches to solve the problem with d-relaxed priority rule. We improve the mathematical formulation proposed in the literature to construct an exact solution method. A metaheuristic method based on the framework of iterated local search with problem-tailored operators is also introduced to find approximate solutions. Experimental results show the effectiveness of our methods.

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Metaheuristics for the tabu clustered traveling salesman problem

Cited by 23 publications

References 21 publications

The Generalized Median Tour Problem: Modeling, Solving and an Application

The Generalized Median Tour Problem: Modeling, Solving and an Application

Transmission Line Planning Based on Artificial Intelligence in Smart Cities

Solving the clustered traveling salesman problem with ‐relaxed priority rule

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