Algorithmic multi-objective heuristics construction in the A* search

Merging multi-objective optimization and expert systems technology results in reduced modeling efforts and enhanced problem-solving tools. Search is one of the ways to combine multi-objective optimization and knowledge-intensive computation schemes. Search is usually associated with prohibitive computational costs and heuristics are often used to alleviate the computational burden. The paper proposes an efficient algorithm for constructing multi-objective heuristics. It also develops some sufficiency conditions for the admissibility of the heuristic. The present multi-objective A* algorithm has been implemented and experimentally evaluated. Its time performance is comparable and often superior to that of other more conventional algorithms.