The travelling thief problem: The first step in the transition from theoretical problems to realistic problems

Bonyadi, Mohammad Reza; Michalewicz, Zbigniew; Barone, Luigi

doi:10.1109/cec.2013.6557681

Cited by 119 publications

(112 citation statements)

References 17 publications

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“…In particualr we want to explore the effect of this aproach on problems containing multiple interdependent sub-problems, using the Travelling Thief Problem [8] as an example. It seems that increased population diversity would especially improve the performance of the genetic algorithm for such compound hard optimisation problems.…”

Section: B Motivationmentioning

confidence: 99%

DiverGene: Experiments on Controlling Population Diversity in Genetic Algorithm with a Dispersion Operator

Strzezek

Trammer

Sydow

2015

Annals of Computer Science and Information Systems

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Abstract-We present diverGene -a novel, diversity-aware population selection operator for genetic algorithm -to be used especially for particularly complex and multi-criteria optimisation problems. Genetic algorithm is one of the most known evolutionary algorithms for solving hard optimisation problems. Many attempts have been made to improve its convergence rate and quality of the result. In this paper we propose a novel extension of the selection operator that makes it possible to control the level of diversity in the population. We discuss its theoretical background, including its computational hardness and propose an efficient way of computing it. The approach is implemented and tested on three hard optimisation problems: Knapsack Problem, Travelling Salesman Problem and a relatively new Travelling Thief Problem that might be viewed as the composition of the latter two. We report experimental results that seem to indicate that the novel approach has a potential to improve the quality of the results for some hard optimisation problems.

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Section: B Motivationmentioning

confidence: 99%

DiverGene: Experiments on Controlling Population Diversity in Genetic Algorithm with a Dispersion Operator

Strzezek

Trammer

Sydow

2015

Annals of Computer Science and Information Systems

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“…From an optimisation perspective, the aforementioned concept consists of two interdependent optimisation problems, which are also known as multicomponent optimisation problems (Bonyadi et al, 2013):…”

Section: A Multi-objective and Multi-component (Momc) Approachmentioning

confidence: 99%

A real-time Active Routing approach via a database for airport surface movement

Weiszer

Chen

Stewart

2015

Transportation Research Part C: Emerging Technologies

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Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process.

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“…Take TTP as an example, in Bonyadi et al (2013), a simple decomposition of TTP into TSP and KP was designed by setting…”

Section: Problem Analysismentioning

confidence: 99%

“…Standard crossover and mutation operators are employed. The proposed algorithms were compared on the benchmark instances proposed in Bonyadi et al (2013), and the results showed that MA managed to obtain much better solutions than CC for all the test instances. In other words, with the same crossover and mutation operators for each sub-problem, a more proper way of integrating the optimization process of the sub-problems can result in a significantly better solution.…”

Section: Introductionmentioning

confidence: 99%

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On investigation of interdependence between sub-problems of the Travelling Thief Problem

Mei

Yao

2014

Soft Comput

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In this paper, the interdependence between subproblems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP.

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The travelling thief problem: The first step in the transition from theoretical problems to realistic problems

Cited by 119 publications

References 17 publications

DiverGene: Experiments on Controlling Population Diversity in Genetic Algorithm with a Dispersion Operator

DiverGene: Experiments on Controlling Population Diversity in Genetic Algorithm with a Dispersion Operator

A real-time Active Routing approach via a database for airport surface movement

On investigation of interdependence between sub-problems of the Travelling Thief Problem

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