The Traveling Tournament Problem (TTP) schedules a double roundrobin tournament to minimize the total distance traveled by competing teams. It involves issues of feasibility and optimality and is challenging for both constraint programming and integer programming. This paper considers the TTP proposed in [4],[[12]. We divide the search space into two subspaces. Simulated Annealing (SA) is used ...

Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners is NP-complete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bid ordering heuristics, and a host of str...

In [6] solutions for the nesting problem are produced using the No Fit Polygon (NFP), simulated annealing (SA) and a new evaluation method. It showed that SA could out perform hill climbing, thus suggesting that evolutionary approaches produce better solutions than a standard search algorithm. In this paper this work is developed. Genetic algorithms (GA) and tabu search (TS) are compared with t...

Generalized hill climbing algorithms provide a framework for modeling several local search algorithms for hard discrete optimization problems. This paper introduces and analyzes generalized hill climbing algorithm performance measures that reflect how effectively an algorithm has performed to date in visiting a global optimum and how effectively an algorithm may perform in the future in visitin...

The Hermite collocation method of discretization can be used to determine highly accurate solutions to the steady state one-dimensional convection-diffusion equation (which can be used to model the transport of contaminants dissolved in groundwater). This accuracy is dependent upon sufficient refinement of the finite element mesh as well as applying upstream weighting to the convective term thr...

This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and ...

In this paper, the introduction of a homeostatic regulation mechanism in a vision system is proposed. This homeostatic mechanism takes charge of controlling the luminance, white balance, contrast and size of the object of interest in the image, using naive methods except for the contrast, for which we have implemented a method that avoids the hill climbing search for the best focus position. We...

Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of ...

In my youth I used to wander in the mountains. I would gain a "feel" of the terrain and gradually build up a reliable intuition of how to get from here to there and back again. Always, on these expeditions, I would discover special places a tiny area, the only one, where fairy slippers grew; a pool in a rushing stream that was deep enough to swim in. Invariably I would find myself excitedly cli...

The iPDB procedure by Haslum et al. is the stateof-the-art method for computing additive abstraction heuristics for domain-independent planning. It performs a hill-climbing search in the space of pattern collections, combining information from multiple patterns in the so-called canonical heuristic. We show how stronger heuristic estimates can be obtained through linear programming. An experimen...