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Abstract: The problem of finding time series discord has attracted much attention recently due to its numerous applications and several algorithms have been suggested. However, most of them suffer from high computation cost and cannot satisfy the requirement of real applications. In this paper, we propose a novel discord discovery algorithm BitClusterDiscord which is based on bit representation clustering. Firstly, we use PAA (Piecewise Aggregate Approximation) bit serialization to segment time series, so as to capture the main variation characteristic of time series and avoid the influence of noise. Secondly, we present an improved K-Medoids clustering algorithm to merge several patterns with similar variation behaviors into a common cluster. Finally, based on bit representation clustering, we design two pruning strategies and propose an effective algorithm for time series discord discovery. Extensive experiments have demonstrated that the proposed approach can not only effectively find discord of time series, but also greatly improve the computational efficiency. [Copyright &y& Elsevier]

Abstract: Vehicle routing problems are at the heart of most decision support systems for real-life distribution problems. In vehicle routing problem a set of routes must be determined at lowest total cost for a number of resources (i.e. fleet of vehicles) located at one or several points (e.g. depots, warehouses) in order to efficiently service a number of demand or supply points. In this paper an efficient evolution strategies algorithm is developed for both capacitated vehicle routing problem and for vehicle routing problem with time window constraints. The algorithm is based on a new multi-parametric mutation procedure that is applied within the 1+1 evolution strategies algorithm. Computational testing on six real-life problems and 195 benchmark problems demonstrate that the suggested algorithm is efficient and highly competitive, improving or matching the current best-known solution in 42% of the test cases. [Copyright &y& Elsevier]

Threshold Accepting, a variant of Simulated, Annealing, is applied for the first time to a set of 356 benchmark instances for the Vehicle Routing with Time Windows. The Threshold Accepting metaheuristic is used to improve upon results obtained with a recent parallel genetic algorithm and a multi-start local search to illustrate its value as a post-processor. The Threshold Accepting metaheuristic is shown to be a fast and versatile post-processor that can be imposed upon a variety of heuristic or metaheuristic approaches for vehicle routing to get better results in both theoretical and practical application. [ABSTRACT FROM AUTHOR]

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