An Experimental Study of Estimation-based Metaheuristics for the Probabilistic Traveling Salesman Problem
نویسندگان
چکیده
The probabilistic traveling salesman problem (PTSP), a paradigmatic example of a stochastic combinatorial optimization problem, is used to study routing problems under uncertainty. Recently, we introduced a new estimation-based iterative improvement algorithm for the PTSP and we showed that it outperforms for a number of instance classes the previous state-of-the-art algorithms. In this paper, we integrate this estimation-based iterative improvement algorithm into some metaheuristics to solve the PTSP and we study their performance.
منابع مشابه
Estimation-based metaheuristics for the probabilistic traveling salesman problem
The probabilistic traveling salesman problem (PTSP) is a central problem in stochastic routing. Recently, we have shown that empirical estimation is a promising approach to devise highly effective local search algorithms for the PTSP. In this paper, we customize two metaheuristics, an iterated local search algorithm and a memetic algorithm, to solve the PTSP. This customization consists in adop...
متن کاملSolving Traveling Salesman Problem based on Biogeography-based Optimization and Edge Assembly Cross-over
Biogeography-Based Optimization (BBO) algorithm has recently been of great interest to researchers for simplicity of implementation, efficiency, and the low number of parameters. The BBO Algorithm in optimization problems is one of the new algorithms which have been developed based on the biogeography concept. This algorithm uses the idea of animal migration to find suitable habitats for solvin...
متن کاملSampling Strategies and Local Search for Stochastic Combinatorial Optimization
In recent years, much attention has been devoted to the development of metaheuristics and local search algorithms for tackling stochastic combinatorial optimization problems. In this paper, we propose an effective local search algorithm that makes use of empirical estimation techniques for a class of stochastic combinatorial optimization problems. We illustrate our approach and assess its perfo...
متن کاملEstimation-Based Local Search for Stochastic Combinatorial Optimization Using Delta Evaluations: A Case Study on the Probabilistic Traveling Salesman Problem
I recent years, much attention has been devoted to the development of metaheuristics and local search algorithms for tackling stochastic combinatorial optimization problems. This paper focuses on local search algorithms; their effectiveness is greatly determined by the evaluation procedure that is used to select the best of several solutions in the presence of uncertainty. In this paper, we pro...
متن کاملAn Approach for Solving Traveling Salesman Problem
In this paper, we introduce a new approach for solving the traveling salesman problems (TSP) and provide a solution algorithm for a variant of this problem. The concept of the proposed method is based on the Hungarian algorithm, which has been used to solve an assignment problem for reaching an optimal solution. We introduced a new fittest criterion for crossing over such problems, and illu...
متن کامل