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

Author(s):  
Mohamed Abdellahi Amar ◽  
Walid Khaznaji

<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>

2020 ◽  
Author(s):  
Mohamed Abdellahi Amar ◽  
Walid Khaznaji

<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>


1997 ◽  
Vol 2 (3) ◽  
pp. 187-200 ◽  
Author(s):  
Gilbert Laporte ◽  
Jean-Yves Potvin ◽  
Florence Quilleret

Author(s):  
Chuanwei Zhang ◽  
Feiyan Han ◽  
Wu Zhang

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%.


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