An Overview of Use of Linear Data Structure in Heuristic Search Technique
Girish P Potdar, Ravindra C. Thool · 2013
Abstract — Search problems can be classified by the amount of information that is available to the search process. When no information is known a priori, a search program must perform blind or uninformed search. When more information than initial state, operator and the goal test is available the size of search space can usually be constrained. These methods are known as informed search methods. These often depend on use of heuristic information. A heuristic is a rule of thumb, strategy, trick, simplification or any other kind of device which drastically limits search for solutions in large problem spaces. Heuristics doesn’t guarantee optimal solutions; in fact they do not guarantee any solution at all; they offer solutions which are good enough most of the time. Optimization is the process of finding the best solution from a set of solutions. In some cases optimization may not be possible or simply not efficient enough to generate solutions in the required time, so heuristic may be used instead. If a problem is solved repetitively and the parameters change often, heuristics are more likely to fall apart. Heuristic performance may be improved by incorporating optimization algorithms. Better solutions are generated for a broader range of parameters by optimizing inside some steps of the heuristic search algorithm. The paper explore different heuristic search techniques and propose a heuristic search method that aims to overcome the drawbacks of existing techniques by making changes in the data structures used in order to achieve best possible solution and to improve the performance efficiency