Showing papers by "Graham Kendall published in 2017"

Improved Local Search Approaches to Solve Post Enrolment Course Timetabling Problem

Abstract: Highlights •Tabu Search with Sampling and Perturbation is efficient in finding feasible solution. •Simulated Annealing with Reheating eliminates extensive tuning and scalable (runtime). •It consists of a novel neighbor examination, local optima detection and reheating. •New best known results for many instances. Abstract In this work, we are addressing the post enrollment course timetabling (PE-CTT) problem. We combine different local search algorithms into an iterative two stage procedure. In the first stage, Tabu Search with Sampling and Perturbation (TSSP) is used to generate feasible solutions. In the second stage, we propose an improved variant of Simulated Annealing (SA), which we call Simulated Annealing with Reheating (SAR), to improve the solution quality of feasible solutions. SAR has three features: a novel neighborhood examination scheme, a new way of estimating local optima and a reheating scheme. SAR eliminates the need for extensive tuning as is often required in conventional SA. The proposed methodologies are tested on the three most studied datasets from the scientific literature. Our algorithms perform well and our results are competitive, if not better, compared to the benchmarks set by the state of the art methods. New best known results are provided for many instances. Keywords Timetabling; Combinatorial Optimization; Local Search; Tabu Search with Sampling and Perturbation (TSSP); Simulated Annealing with Reheating (SAR)

A Hyperheuristic Methodology to Generate Adaptive Strategies for Games

Abstract: Hyperheuristics have been successfully applied in solving a variety of computational search problems. In this paper, we investigate a hyperheuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyperheuristic game player can generate strategies which adapt to both the behavior of the co-players and the game dynamics. By using a simple heuristic selection mechanism, a number of existing heuristics for specialized games can be integrated into an automated game player. As examples, we develop hyperheuristic 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.

A scheme for determining vehicle routes based on Arc-based service network design

Abstract: In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time However, the Node-Arc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures that the number of outgoing vehicles equals the number of incoming vehicles at each node How to transform the optimized service network into a set of vehicle routes remains an important problem that has not yet been studied In this paper, we propose a three-phase scheme to address this problem In the first stage, we present an algorithm based on the depth-first search to find all of the different cyclic routes in a service network design solution In the second stage, we propose to prune poor cyclic routes using real-life constraints so that a collection of acceptable vehicle routes can be obtained before route assignment Some of the pruning can also be done in the first stage to speed up the proposed algorithm In the third stage, we formulate the problem of selecting a set of cyclic routes to cover the entire network as a weighted set covering problem The resulting model is formulated as an integer program and solved with IBM ILOG CPLEX solver Experimental results on benchmark instances for service network design indicate the effectiveness of the proposed scheme which gives high-quality solutions in an efficient way

Shrimp Feed Formulation via Evolutionary Algorithm with Power Heuristics for Handling Constraints

Abstract: Formulating feed for shrimps represents a challenge to farmers and industry partners. Most previous studies selected from only a small number of ingredients due to cost pressures, even though hundreds of potential ingredients could be used in the shrimp feed mix. Even with a limited number of ingredients, the best combination of the most appropriate ingredients is still difficult to obtain due to various constraint requirements, such as nutrition value and cost. This paper proposes a new operator which we call Power Heuristics, as part of an Evolutionary Algorithm (EA), which acts as a constraint handling technique for the shrimp feed or diet formulation. The operator is able to choose and discard certain ingredients by utilising a specialized search mechanism. The aim is to achieve the most appropriate combination of ingredients. Power Heuristics are embedded in the EA at the early stage of a semirandom initialization procedure. The resulting combination of ingredients, after fulfilling all the necessary constraints, shows that this operator is useful in discarding inappropriate ingredients when a crucial constraint is violated.

We should be just a number, and we should embrace it

Abstract: Purpose - This viewpoint article supports the use of unique identifiers for the authors of scientific publications. This, we believe, aligns with the views of many others as it would solve the problem of author disambiguation. If every researcher had a unique identifier there would be significant opportunities to provide even more services. These extensions are proposed in this paper. Design/methodology/approach - We discuss the bibliographic services that are currently available. This leads to a discussion of how these services could be developed and extended. Findings - We suggest a number of ways that a unique identifier for scientific authors could support many other areas of importance to the scientific community. This will provide a much more robust system that provides a much richer, and more easily maintained, scientific environment. Originality/value - The scientific community lags behind most other communities with regard to the way it identfies individuals. Even if the current vision for a unique identifier for authors were to become more widespread, there would still be many areas where the community could improve its operations. This viewpoint paper suggests some of these, along with a financial model that could underpin the functionality

Evaluating decision making units under uncertainty using fuzzy multi-objective nonlinear programming

Abstract: This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fuzzy Data Envelopment Analysis (DEA). In the proposed multi-objective nonlinear programming methodology both the objective functions and the constraints are considered fuzzy. The coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.

Supplementary Material for the Information Sciences Paper: An Experimental Study of Hyper-Heuristic Selection and Acceptance Mechanism for Combinatorial t-way Test Suite Generation

Abstract: Software testing relates to the process of accessing the functionality of a program against some defined specifications. To ensure conformance, test engineers often generate a set of test cases to validate against the user requirements. Owing to the growing complexity of software and its increasing diffusion into various application domains, it is no longer unusual for a software project to have testing teams in more than one location or even distributed over many continents. Owing to the intertwined dependencies of many software development activities and their geographical and temporal issues, there are potentially many overlapping test cases which can cause unwarranted redundancies across the shared modules (i.e. a test for one requirement may be covered by more than one test). In this paper, we explore the application of our newly developed hyperheuristic, called Fuzzy Inference Selection (FIS), for addressing test redundancy reduction problem. This paper presents the supplementary results for the paper : An Experimental Study of Hyper-Heuristic Selection and Acceptance Mechanism for Combinatorial t way Test Suite Generation published in Information Sciences.