397 research outputs found

    Evolving Diverse Sets of Tours for the Travelling Salesperson Problem

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    Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this area of research by examining evolutionary diversity optimisation approaches for the classical Traveling Salesperson Problem (TSP). We study the impact of using different diversity measures for a given set of tours and the ability of evolutionary algorithms to obtain a diverse set of high quality solutions when adopting these measures. Our studies show that a large variety of diverse high quality tours can be achieved by using our approaches. Furthermore, we compare our approaches in terms of theoretical properties and the final set of tours obtained by the evolutionary diversity optimisation algorithm.Comment: 11 pages, 3 tables, 3 figures, to be published in GECCO '2

    Evolutionary Diversity Optimisation for The Traveling Thief Problem

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    There has been a growing interest in the evolutionary computation community to compute a diverse set of high-quality solutions for a given optimisation problem. This can provide the practitioners with invaluable information about the solution space and robustness against imperfect modelling and minor problems' changes. It also enables the decision-makers to involve their interests and choose between various solutions. In this study, we investigate for the first time a prominent multi-component optimisation problem, namely the Traveling Thief Problem (TTP), in the context of evolutionary diversity optimisation. We introduce a bi-level evolutionary algorithm to maximise the structural diversity of the set of solutions. Moreover, we examine the inter-dependency among the components of the problem in terms of structural diversity and empirically determine the best method to obtain diversity. We also conduct a comprehensive experimental investigation to examine the introduced algorithm and compare the results to another recently introduced framework based on the use of Quality Diversity (QD). Our experimental results show a significant improvement of the QD approach in terms of structural diversity for most TTP benchmark instances.Comment: To appear at GECCO 202

    A comparative study of evolutionary approaches to the bi-objective dynamic Travelling Thief Problem

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    Dynamic evolutionary multi-objective optimization is a thriving research area. Recent contributions span the development of specialized algorithms and the construction of challenging benchmark problems. Here, we continue these research directions through the development and analysis of a new bi-objective problem, the dynamic Travelling Thief Problem (TTP), including three modes of dynamic change: city locations, item profit values, and item availability. The interconnected problem components embedded in the dynamic problem dictate that the effective tracking of good trade-off solutions that satisfy both objectives throughout dynamic events is non-trivial. Consequently, we examine the relative contribution to the non-dominated set from a variety of population seeding strategies, including exact solvers and greedy algorithms for the knapsack and tour components, and random techniques. We introduce this responsive seeding extension within an evolutionary algorithm framework. The efficacy of alternative seeding mechanisms is evaluated across a range of exemplary problem instances using ranking-based and quantitative statistical comparisons, which combines performance measurements taken throughout the optimization. Our detailed experiments show that the different dynamic TTP instances present varying difficulty to the seeding methods tested. We posit the dynamic TTP as a suitable benchmark capable of generating problem instances with different controllable characteristics aligning with many real-world problems

    Evolutionary Diversity Optimisation for Combinatorial Problems

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    Diversity optimisation explores a variety of solutions for the intended problem and is rapidly growing and getting more popular within the evolutionary computation community as a result. There can be found several studies that introduce and examine evolutionary approaches to compute a diverse set of solutions for optimisation problems in the continuous domain. To the best of our knowledge, the discrete problems are yet to be studied in the context of diversity optimisation. Thus, this thesis focuses on combinatorial optimisation problems with discrete solution spaces. Here, we compute and explore such solution sets for several noticeable combinatorial problems. We aim to introduce and design evolutionary algorithms capable of computing a diverse set of solutions for the given combinatorial optimisation problem. First, we begin with a comprehensive literature review of the recent developments and then dig deep into two prominent diverse paradigms in evolutionary computation: evolutionary diversity optimisation and quality diversity. These concepts have gained a considerable amount of attention in recent years. Quality diversity aims to achieve diversity in behavioural spaces, while evolutionary diversity optimisation sees diversity in the structural properties of solutions. We study the evolutionary algorithms for the travelling salesperson problem, the travelling thief program, the knapsack problem, and finally, the Boolean satisfiability problem. The prospective results demonstrate the capability of the introduced algorithms to achieve diverse and high-quality solutions.Thesis (Ph.D.) -- University of Adelaide, School of Computer and Mathematical Sciences, 202

    A feature-based comparison of local search and the Christofides algorithm for the travelling salesperson problem

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    Understanding the behaviour of well-known algorithms for classical NP-hard optimisation problems is still a difficult task. With this paper, we contribute to this research direction and carry out a feature based comparison of local search and the well-known Christofides approximation algorithm for the Traveling Salesperson Problem. We use an evolutionary algorithm approach to construct easy and hard instances for the Christofides algorithm, where we measure hardness in terms of approximation ratio. Our results point out important features and lead to hard and easy instances for this famous algorithm. Furthermore, our cross-comparison gives new insights on the complementary benefits of the different approaches.Samadhi Nallaperuma, Markus Wagner, Frank Neumann, Bernd Bischl, Olaf Mersmann, Heike Trautmannhttp://www.sigevo.org/foga-2013

    Application of genetic algorithms to the travelling salesperson problem.

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    Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1996.Genetic Algorithms (GAs) can be easily applied to many different problems since they make few assumptions about the application domain and perform relatively well. They can also be modified with some success for handling a particular problem. The travelling salesperson problem (TSP) is a famous NP-hard problem in combinatorial optimization. As a result it has no known polynomial time solution. The aim of this dissertation will be to investigate the application of a number of GAs to the TSP. These results will be compared with those of traditional solutions to the TSP and with the results of other applications of the GA to the TSP

    An exploratory study of Taiwanese long-haul package tour customers' satisfaction

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    Taiwan has achieved rapid and continued economic growth over the last thirty years. This economic prosperity has significantly increased the demand for outbound tourism from Taiwan. However, the immature marketing strategies of travel agencies and lack of experience of both travel agencies and outbound tourists has also increased confrontation between the two parties. This research investigated customer satisfaction/dissatisfaction on pre-tour and on-tour service encounters between Taiwanese travel agencies and their customers. It analysed the role of the tour leader and the relationship with customers on guided group tours, and the link between overall satisfaction with a travel agency and the generation of repeat business. This study adopted exploratory research to investigate the service elements provided by travel agencies and the relative factors that affect tourist satisfaction when customers are taking a long-haul package tour. The primary data was collected using three different research methods: in-depth, semi-structured face-to-face interviews with managers from 19 randomly selected Taiwanese travel agencies; participant observation of a ten day Taiwanese guided group (package) tour to Italy; and semi-structured international telephone interviews with 23 of the Taiwanese tour group participants. Additional data was received from the collaborating travel agency, which had conducted its own research on customer satisfaction on the same tour. The primary data of interview transcripts and field notes were analysed using NUDIST software. The transcripts of the findings and discussion provide a detailed ethnographic study of the experiences, which these Taiwanese tourists encountered on a long-haul package holiday. The findings indicated that Taiwanese travellers are price-sensitive, have limited individual initiative and tend to over-rely on travel agencies and tour leaders. The tour leader's performance is the key factor resulting in customers' complaints or contributing to customers' satisfaction on a tour. However, Taiwan's tour leaders are tip-sensitive and the issue of tipping plays a crucial factor in influencing the tour leaders' job performance as well as customer satisfaction. Many travel agencies indicated that customer satisfaction was not so significant and the tour leader's performance was acceptable - providing customers did not complain. A process for the success of a guided-package tour has been developed to enable travel agencies to deliver a better service, as well as engage in more effective marketing campaigns. The differences in perception between service providers and customers have been identified as an important barrier to customer satisfaction. This model suggests that travel agencies should aim at developing customers' expectations to a realistic level during the pre-tour stage. It also suggests building customers' satisfaction to a reasonable !evel during the on-tour encounter. Changing customer satisfaction from merely satisfied to totally satisfied increases production and operational costs, which may not be a wise investment in terms of the financial return - particularly in an intensely competitive market where customers are price sensitive. The model suggests that travel agencies should be aware of the importance of the tour leaders' service performance and communication skills, to explain to customers the reason why negative incidents of flow significance (NII.'s) occur and consequently to help reduce customer dissatisfaction. This study identified the key influences on customer satisfaction when customers are taking a guided package tour. Components of satisfaction - expectation, performance, attribution, emotion and equity - Identified and examined. An additional component - communication - emerged which appeared to facilitate understanding between customers and service providers. The notion of Round Table Theory was put forward as a tool to illustrate equity from a tourist consumer perspective. The variety of research methods allowed due triangulation and so increased the validity of the research. Empirical findings of this study provide a better understanding of the components of customer satisfaction of a long-haul package tour
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