The Study of Neighborhood Structure of Tabu Search Algorithm for Traveling Salesman Problem

2008 ◽  
Author(s):  
YiWen Zhong ◽  
Chao Wu ◽  
LiShan Li ◽  
ZhengYuan Ning
Keyword(s):  
Tabu Search ◽  
Traveling Salesman Problem ◽  
Search Algorithm ◽  
Traveling Salesman ◽  
Tabu Search Algorithm ◽  
Neighborhood Structure

Study on Tabu Search Algorithm for Multi-Cargo Loading Problem

2012 ◽  
Vol 178-181 ◽  
pp. 1802-1805
Author(s):  
Chun Yu Ren
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Initial Solution ◽  
Neighborhood Search ◽  
Tabu Search Algorithm ◽  
Search Efficiency ◽  
Speed Of Convergence ◽  
Neighborhood Structure ◽  
Loading Problem

The paper is focused on the Multi-cargo Loading Problem (MCLP). Tabu search algorithm is an algorithm based on neighborhood search. According to the features of the problem, the essay centered the construct initial solution to construct neighborhood structure. For the operation, 1-move and 2-opt were applied, it can also fasten the speed of convergence, and boost the search efficiency. Finally, the good performance of this algorithm can be proved by experiment calculation and concrete examples.

A cutting sequence optimization method based on tabu search algorithm for complex parts machining

2018 ◽  
Vol 233 (3) ◽  
pp. 745-755 ◽  
Author(s):  
Chuanwei Zhang ◽  
Feiyan Han ◽  
Wu Zhang
Keyword(s):  
Tabu Search ◽  
Tool Path ◽  
Search Algorithm ◽  
Optimization Method ◽  
Traveling Salesman ◽  
Tabu Search Algorithm ◽  
Rough Machining ◽  
Sequence Optimization ◽  
Cutting Sequence ◽  
Complex Parts

Defining the cutting sequence of each cutter scientifically in the process of removing the allowance has an important influence on the machining efficiency for complex parts, which have multiple machining features. In order to satisfy the needs of high efficiency for rough machining, after determining the tool path of the machining region, a cutting sequence optimization method based on the tabu search algorithm is presented to define the cutting order in rough machining of complex parts. First, a cutting sequence optimization mathematical model is established, which relates to the shortest total length of the tool path. Second, through the problem analysis, the cutting sequence optimization model is converted into an open and constrained traveling salesman problem. And then, the optimization model is solved by dealing with an open and constrained traveling salesman problem using the tabu search algorithm. Finally, the optimal cutting sequence of machining a casing part is calculated, and a simulation and experiment are carried out. The result shows that the optimization approach presented in this article can optimize the cutting sequence and cutter position of advance and retract. Compared with the non-optimized cutting sequence method, the total length of tool path is reduced by 16.7%, the cutter lifting times are reduced to 26, and the efficiency is increased by 21.62%.

Microcanonical Optimization Applied to the Traveling Salesman Problem

1998 ◽  
Vol 09 (01) ◽  
pp. 133-146 ◽  
Author(s):  
Alexandre Linhares ◽  
José R. A. Torreão
Keyword(s):  
Simulated Annealing ◽  
Traveling Salesman Problem ◽  
Optimization Problems ◽  
Search Algorithm ◽  
New Physics ◽  
Traveling Salesman ◽  
Tabu Search Algorithm ◽  
Combinatorial Optimization Problems ◽  
Microcanonical Annealing ◽  
The Traveling Salesman Problem

Optimization strategies based on simulated annealing and its variants have been extensively applied to the traveling salesman problem (TSP). Recently, there has appeared a new physics-based metaheuristic, called the microcanonical optimization algorithm (μO), which does not resort to annealing, and which has proven a superior alternative to the annealing procedures in various applications. Here we present the first performance evaluation of μO as applied to the TSP. When compared to three annealing strategies (simulated annealing, microcanonical annealing and Tsallis annealing), and to a tabu search algorithm, the microcanonical optimization has yielded the best overall results for several instances of the euclidean TSP. This confirms μO as a competitive approach for the solution of general combinatorial optimization problems.

Study on Mechanical Bearing Capacity with Tabu Search Algorithm for Multi-Vehicle and Multi-Cargo Loading Problem

2013 ◽  
Vol 345 ◽  
pp. 3-6
Author(s):  
Chun Yu Ren
Keyword(s):  
Tabu Search ◽  
Bearing Capacity ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Tabu Search Algorithm ◽  
Search Efficiency ◽  
Neighborhood Structure ◽  
Loading Problem ◽  
Annealing Algorithm

This paper studies multi-vehicle and multi-cargo loading problem under the limited mechanical bearing capacity. Tabu search algorithm is an algorithm based on neighborhood search. According to the features of the problem, the essay centered the construct initial solution to construct neighborhood structure. Firstly, for the operation, 1-move and 2-opt were applied. Secondly, through utilizing Boltzmann mechanism of simulated annealing algorithm, it can also fasten the speed of convergence, and boost the search efficiency. Finally, the good performance of this algorithm can be proved by experiment calculation and the mechanical engineering examples.

Study on Tabu Search Algorithm for Min-Max Vehicle Routing Problem

2011 ◽  
Vol 63-64 ◽  
pp. 160-163
Author(s):  
Chun Yu Ren
Keyword(s):  
Tabu Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Tabu Search Algorithm ◽  
Search Efficiency ◽  
Speed Of Convergence ◽  
Neighborhood Structure ◽  
Routing Problem

The paper is focused on the Min-Max Vehicle Routing Problem (MMVRP). Tabu search algorithm is an algorithm based on neighborhood search. According to the features of the problem, the essay centered the longest route to construct neighborhood structure. For the operation, 1-move and 2-opt were applied, it can also fasten the speed of convergence, and boost the search efficiency. Finally, the good performance of this algorithm can be proved by experiment calculation and concrete examples.

scholarly journals Optimal Route Planning for Truck–Drone Delivery Using Variable Neighborhood Tabu Search Algorithm

2022 ◽  
Vol 12 (1) ◽  
pp. 529
Author(s):  
Bao Tong ◽  
Jianwei Wang ◽  
Xue Wang ◽  
Feihao Zhou ◽  
Xinhua Mao ◽  
...  
Keyword(s):  
Tabu Search ◽  
Programming Model ◽  
Search Algorithm ◽  
Mixed Integer ◽  
Tabu Search Algorithm ◽  
Delivery Time ◽  
Neighborhood Structure ◽  
Search Range ◽  
Wide Range ◽  
Delivery Route

The optimal delivery route problem for truck–drone delivery is defined as a traveling salesman problem with drone (TSP-D), which has been studied in a wide range of previous literature. However, most of the existing studies ignore truck waiting time at rendezvous points. To fill this gap, this paper builds a mixed integer nonlinear programming model subject to time constraints and route constraints, aiming to minimize the total delivery time. Since the TSP-D is non-deterministic polynomial-time hard (NP-hard), the proposed model is solved by the variable neighborhood tabu search algorithm, where the neighborhood structure is changed by point exchange and link exchange to expand the tabu search range. A delivery network with 1 warehouse and 23 customer points are employed as a case study to verify the effectiveness of the model and algorithm. The 23 customer points are visited by three truck–drones. The results indicate that truck–drone delivery can effectively reduce the total delivery time by 20.1% compared with traditional pure-truck delivery. Sensitivity analysis of different parameters shows that increasing the number of truck–drones can effectively save the total delivery time, but gradually reduce the marginal benefits. Only increasing either the truck speed or drone speed can reduce the total delivery time, but not to the greatest extent. Bilateral increase of truck speed and drone speed can minimize the delivery time. It can clearly be seen that the proposed method can effectively optimize the truck–drone delivery route and improve the delivery efficiency.

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