Competitive travelling salesmen problem: A hyper-heuristic approach

Kendall, Graham; Li, Jiawei

doi:10.1057/jors.2012.37

Cited by 26 publications

(17 citation statements)

References 12 publications

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“…Here, the salesperson is free to choose which cities to visit in order to maximize the profit while minimizing the travelling cost. Among such studies are Fekete, Fleischer, Fraenkel, and Schmitt (); Filippi and Stevanato (); Grimme, Meisel, Trautmann, Rudolph, and Wölck (); Keller and Goodchild (); Kendall and Li (); and Mohtadi and Nogondarian ().…”

Section: The Travelling Salesman Problem As a Mogmentioning

confidence: 99%

“…When there is more than one salesperson, the TSP is posed as a game between salespersons, which may belong to either a competitive game type (e.g. Fekete et al, 2004;Kendall & Li, 2012) or to a cooperative game type (e.g., Mohtadi & Nogondarian, 2014;Qu, Yi, & Tang, 2007). Salespersons often have to compete with those of rival companies.…”

Section: Tsp As a Competitive Game Problemmentioning

confidence: 99%

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Decision‐making in non‐cooperative games with conflicting self‐objectives

Eisenstadt

Moshaiov

2018

Multi Criteria Decision Anal

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This paper concerns multicriteria decision making by players in a conflict situation. The considered situation is modelled as a non‐cooperative game. Moreover, the player has a conflict not only with the opponent, but also she is faced with her own conflicting objectives. Hence, selecting a strategy is dependent on both objective preferences and the inherent uncertainty about the opponent selection. In contrast to most studies on such multiobjective games (MOGs), which employed a scalarization approach, it has recently been suggested to pose such games as MOGs with undecided objective preferences. As in Pareto optimization, the novel solution method to the considered MOGs reveals tradeoff information, which is commonly hindered when using a classical scalarization approach. To complement and highlight the significance of the aforementioned approach, two decision analysis techniques are suggested. The proposed techniques are compared with weighted‐sum utility‐based analysis, as well as with the Pareto‐optimal security strategy approach. The comparison is done using a MOG with two competing travelling salesperson. It is concluded that the suggested techniques allow incorporating tradeoff information to justify the selection of a strategy.

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Section: The Travelling Salesman Problem As a Mogmentioning

confidence: 99%

Section: Tsp As a Competitive Game Problemmentioning

confidence: 99%

Decision‐making in non‐cooperative games with conflicting self‐objectives

Eisenstadt

Moshaiov

2018

Multi Criteria Decision Anal

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“…Hyper-heuristics encompass a set of approaches with the goal of automating the design and tuning of heuristic methods to solve hard search problems [5] [20]. Hyper-heuristics are considered to be methodologies to build systems which can handle different classes of search problems using the same algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…For example, a hyperheuristic for the competitive travelling salesmen game [20]; an evolutionary-based hyper-heuristic algorithm for the jawbreaker puzzle [38] and hyper-heuristic based solvers for RushHour and FreeCell games [19]. It has been shown that a hyperheuristic is able to generate efficient strategies compared to just using the low-level heuristics in isolation [19].…”

Section: Introductionmentioning

confidence: 99%

A Hyperheuristic Methodology to Generate Adaptive Strategies for Games

Kendall

2017

IEEE Trans. Comput. Intell. AI Games

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Hyper-heuristics have been successfully applied in solving a variety of computational search problems. In this study, we investigate a hyper-heuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyper-heuristic game player can generate strategies which adapt to both the behaviour of the co-players and the game dynamics. By using a simple heuristic selection mechanism, a number of existing heuristics for specialised games can be integrated into an automated game player. As examples, we develop hyper-heuristic game players for three games: iterated prisoner's dilemma, repeated Goofspiel and the competitive traveling salesmen problem. The results demonstrate that a hyperheuristic game player outperforms the low-level heuristics, when used individually in game playing and it can generate adaptive strategies even if the low-level heuristics are deterministic. This methodology provides an efficient way to develop new strategies for games based on existing strategies.

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“…A Nash equilibrium in the street hailing problem is a stable matching between taxi drivers and passengers such that no taxi driver can be better off by changing their chosen passenger. There has previously been some applications of equilibrium analysis in logistic and scheduling (Ishii et al 2012, Kendall andLi 2013).…”

Section: Introductionmentioning

confidence: 99%

A novel approach to independent taxi scheduling problem based on stable matching

Bai

Atkin

et al. 2014

Journal of the Operational Research Society

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This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance to Chinese cities, where hailing a taxi on the street is by far the most common way in which taxis are requested, since the majority of taxi drivers operate independently, rather than working for a company. The mobile phone and GPS-based taxi scheduling system, which is described in this paper, aims to provide a decision support system for taxi drivers and facilitates direct information exchange between taxi drivers and passengers, while allowing drivers to remain independent. The taxi scheduling problem is considered to be a non-cooperative game between taxi drivers and a description of this problem is given. We adopt an efficient algorithm to discover a Nash equilibrium, such that each taxi driver and passenger cannot benefit from changing their assigned partner. Two computational examples are given to illustrate the effectiveness of the approach.

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Competitive travelling salesmen problem: A hyper-heuristic approach

Cited by 26 publications

References 12 publications

Decision‐making in non‐cooperative games with conflicting self‐objectives

Decision‐making in non‐cooperative games with conflicting self‐objectives

A Hyperheuristic Methodology to Generate Adaptive Strategies for Games

A novel approach to independent taxi scheduling problem based on stable matching

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