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Variable neighborhood search algorithm
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Part 1 of ebook "Search methodologies: Introductory tutorials in optimization and decision support techniques" provides readers with contents including: classical techniques; integer programming; genetic algorithms; scatter search; genetic programming; artificial immune systems; swarm intelligence; tabu search; simulated annealing; GRASP: greedy randomized adaptive search procedures; variable neighborhood search;...
344p
thamnhuocgiai
24-09-2023
6
4
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The Multi-stripe Travelling Salesman Problem (Ms-TSP) is an extension of the Travelling Salesman Problem (TSP). In the q-stripe TSP with q ≥ 1, the objective function sums the costs for traveling from one vertex to each of the next q vertices along the tour. To solve medium to large-sized instances, a metaheuristic approach is proposed. The proposed method has two main components, which are construction and improvement phases. The construction phase generates an initial solution using the Greedy Randomized Adaptive Search Procedure (GRASP).
18p
nguathienthan9
08-12-2020
13
2
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This article discusses the ecological vehicle routing problem with a stop at a refueling station titled Green-Vehicle Routing Problem. In this problem, the refueling stations and the limit of fuel tank capacity are considered for the construction of a tour. We propose a variable neighborhood search to solve the problem.
10p
toritori
11-05-2020
17
2
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In particular, almost all feasible instances of the problem are solvable in O(n) time using the new algorithm, where n is the number of vertices. The developed approach also helps in fast enumeration of a neighborhood in the local search and yields an integer programming model with O(n) binary variables for the problem.
12p
danhnguyentuongvi27
19-12-2018
26
0
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Research in the field of vehicle routing is often focused on finding new ideas and concepts in the development of fast and efficient algorithms for an improved solution process. Early studies introduce static tailor-made strategies, but trends show that algorithms with generic adaptive policies - which emerged in the past years - are more efficient to solve complex vehicle routing problems.
16p
vinguyentuongdanh
19-12-2018
38
2
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The uniting feature of combinatorial optimization and extremal graph theory is that in both areas one should find extrema of a function defined in most cases on a finite set. While in combinatorial optimization the point is in developing efficient algorithms and heuristics for solving specified types of problems, the extremal graph theory deals with finding bounds for various graph invariants under some constraints and with constructing extremal graphs.
8p
vinguyentuongdanh
20-12-2018
45
0
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In our work, we propose a metaheuristic algorithm which is mainly based on the principles of Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) to solve the problem. The GRASP is used to build an initial solution which is good enough in a construction phase.
17p
thuyliebe
05-10-2018
46
2
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