A hybrid scatter search for the probabilistic traveling salesman problem

Liu, Yu-Hsin

doi:10.1016/j.cor.2005.11.008

Cited by 54 publications

(31 citation statements)

References 26 publications

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“…Bianchi et al (2002a,b) proposed pACS, an ant colony system (ACS) (Dorigo and Gambardella, 1997) that adopts Equation 1 to compute the cost of solutions. Guntsch (2003, 2004) and Liu (2007Liu ( , 2008 used a truncated version of Equation 1 in pACS and in a scatter search algorithm, respectively. Bianchi (2006) and Bianchi and Gambardella (2007) integrated 1-shift, an analytical computation local search algorithm, into pACS and showed that the resulting pACS+1-shift algorithm is very effective.…”

Section: The Probabilistic Traveling Salesman Problemmentioning

confidence: 99%

Estimation-based metaheuristics for the probabilistic traveling salesman problem

Balaprakash

Birattari

Stützle

et al. 2010

Computers & Operations Research

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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 adopting the estimation approach to evaluate the solution cost, exploiting a recently developed estimationbased local search algorithm, and tuning the metaheuristics parameters. We present an experimental study of the estimation-based metaheuristic algorithms on a number of instance classes. The results show that the proposed algorithms are highly effective and that they define a new state-of-the-art for the PTSP.

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Section: The Probabilistic Traveling Salesman Problemmentioning

confidence: 99%

Estimation-based metaheuristics for the probabilistic traveling salesman problem

Balaprakash

Birattari

Stützle

et al. 2010

Computers & Operations Research

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“…Ello se debió a que el VMC es un método clásico en el TSP, usado con frecuencia para el inicio de otros algoritmos (JÜNGER; REINELT; RINALDI, 1995;LIU, 2007;GÓMEZ;LEÓN, 2011), al cual no se le ha dado una interpretación desde las leyes del pensamiento sistémico. Esto puede ser pertinente, puesto que la regla del VMC parte del sentido común, se destaca por su eficiencia computacional, a costa del deterioro en la respuesta arrojada (BENTLEY, 1992;MARTI, 2003).…”

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Sacrificio cortoplacista adaptativo 2opt (SCA_2opt): Una heurística inspirada en el pensamiento sistémico

Rave¹,

Álvarez²

2013

Prod.

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Outlining two novice heuristics for the symmetric TSP, inspired systemic thinking: Sacrifice short-term adaptive 2-opt (SCA2opt) and SCA_2opt_r. These arise from the systemic analysis of the rule of decision, nearest neighbour, identifying the archetype "Counterproductive solutions". SCA relies on that agent traveler, renounces at any given time immediately to a nearby city, and moves towards the second nearest available city. From there, it continues with the nearest neighbour rule. Each is the SCA (global search) operates a local search 2opt. Where as the binomial effectiveness and efficiency, the two new heuristics are shown promising in comparison multicriteria against 19 metaheuristics. It is evident that systemic thinking is a field of inspiration viable for the development of combinatorial optimization methods; emerging questions for future developments are expressed, enabling to continue to integrate elements of the classical optimization with the systemic thought; areas traditionally seen as antagonistic, but whose dialogue is favourable in this article.

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“…The Queen as well as the the best performing scheme obtained in the study are compared against the previous studies in this section. The heterogeneous PTSP data generated by Tang & Miller-Hooks (2004) has been investigated in several studies (Tang & Miller-Hooks, 2004;Liu, 2006Liu, , 2007Liu, , 2008. The best average E[τ] values as well as the corresponding average CPU time in these studies (Previous Best) are listed in Table 3.…”

Section: Inferential Statistics Analysis Of Nine Selection Schemes Fomentioning

confidence: 99%

“…CPU is the average CPU running time in seconds. The "Previous Best" results for the heterogeneous PTSP data were obtained by Liu (2006Liu ( , 2007Liu ( , 2008, except for n = 50 and p = 0.5, which were obtained by Tang & Miller-Hooks (2004). In Liu's studies (as well as the results of this study), all implementations were performed on an Intel Pentium IV 2.8 GHz CPU personal computer with 512 MB memory (3479 MFlops), while TMH's study was based on a 10-run average and was conducted on a DEC AlphaServer 1200/533 computer with 1 GB memory (1277 MFlops).…”

Section: Inferential Statistics Analysis Of Nine Selection Schemes Fomentioning

confidence: 99%

“…Unlike traditional selection mechanisms used in GA which selects both parents from the entire population based on their fitness values, the queen GA creates a subgroup of better solutions (the queen cohort), and uses at least one of its members in each performed crossover. To validate the effectiveness and efficiency of the proposed algorithmic procedure, a set of heterogeneous (90 instances) and homogeneous (270 instances) PTSP test instances as used in the previous studies (Liu, 2006(Liu, , 2007(Liu, , 2008Tang & Miller-Hooks, 2004) will be used as the base for comparison purpose. The remainder of this chapter is organized as follows.…”

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confidence: 99%

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A hybrid scatter search for the probabilistic traveling salesman problem

Cited by 54 publications

References 26 publications

Estimation-based metaheuristics for the probabilistic traveling salesman problem

Estimation-based metaheuristics for the probabilistic traveling salesman problem

Sacrificio cortoplacista adaptativo 2opt (SCA_2opt): Una heurística inspirada en el pensamiento sistémico

Solving the Probabilistic Travelling Salesman Problem Based on Genetic Algorithm with Queen Selection Scheme

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