An application of Google Map and tabu-search Algorithm for Traveling Salesman Problem on Tel-Home Care

2011 ◽  
Author(s):  
Hung-Chang Lee ◽  
Nan-Ching Huang ◽  
Huan-Chao Keh ◽  
Wei-Hsuan Chang
Keyword(s):  
Tabu Search ◽  
Home Care ◽  
Traveling Salesman Problem ◽  
Search Algorithm ◽  
Traveling Salesman ◽  
Tabu Search Algorithm

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.

scholarly journals An application and Parallel Tabu Search Algorithm for Solving the PTSP Under the OpenMP-MPI Environment

2020 ◽  
Author(s):  
Mohamed Abdellahi Amar ◽  
Walid Khaznaji
Keyword(s):  
Tabu Search ◽  
Traveling Salesman Problem ◽  
Search Algorithm ◽  
A Priori ◽  
Traveling Salesman ◽  
Deterministic Models ◽  
Expected Length ◽  
Np Complete ◽  
Parallel Tabu Search ◽  
Real World Problems

<div>This paper reviews some real-world problems modeling</div><div>as Probabilistic Traveling Salesman Problem (PTSP), by</div><div>presenting the important results found in the literature. It</div><div>illustrates the usefulness of the inclusion of probabilistic elements in deterministic models. We propose a new modeling of the PTSP by the deviations of the routing of a robot in order to avoid obstacles which are not foreseen in its path. The Probabilistic Traveling Salesman Problem(PTSP) is a variation of the classic Traveling Salesman Problem (TSP) where each node i is present</div><div>with probability pi. The solution for the PTSP consists in finding an a priori tour that visits all the cities that minimizes the expected length of the tour. From the litterateur the PTSP is NP-Complete, therefore the execution time is a prime factor in its resolution. In the last of his paper we present a new parallel Tabu search heuristic for solving PTSP by using the Open MPI environment.</div>

scholarly journals An application and Parallel Tabu Search Algorithm for Solving the PTSP Under the OpenMP-MPI Environment

2020 ◽  
Author(s):  
Mohamed Abdellahi Amar ◽  
Walid Khaznaji
Keyword(s):  
Tabu Search ◽  
Traveling Salesman Problem ◽  
Search Algorithm ◽  
A Priori ◽  
Traveling Salesman ◽  
Deterministic Models ◽  
Expected Length ◽  
Np Complete ◽  
Parallel Tabu Search ◽  
Real World Problems

<div>This paper reviews some real-world problems modeling</div><div>as Probabilistic Traveling Salesman Problem (PTSP), by</div><div>presenting the important results found in the literature. It</div><div>illustrates the usefulness of the inclusion of probabilistic elements in deterministic models. We propose a new modeling of the PTSP by the deviations of the routing of a robot in order to avoid obstacles which are not foreseen in its path. The Probabilistic Traveling Salesman Problem(PTSP) is a variation of the classic Traveling Salesman Problem (TSP) where each node i is present</div><div>with probability pi. The solution for the PTSP consists in finding an a priori tour that visits all the cities that minimizes the expected length of the tour. From the litterateur the PTSP is NP-Complete, therefore the execution time is a prime factor in its resolution. In the last of his paper we present a new parallel Tabu search heuristic for solving PTSP by using the Open MPI environment.</div>

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