Parallel Search Algorithms for Discrete Optimization Problems

Abstract

Discrete optimization problems (DOPs) arise in various applications such as planning, scheduling, computer aided design, robotics, game playing and constraint directed reasoning. Often, a DOP is formulated in terms of finding a (minimum cost) solution path in a graph from an initial node to a goal node and solved by graph/tree search methods. Availability of parallel computers has created substantial interest in exploring parallel formulations of these graph and tree search methods. This article provides a survey of various parallel search algorithms such as Backtracking, IDA*, A*, Branch-and-Bound techniques and Dynamic Programming. It addresses issues related to load balancing, communication costs, scalability and the phenomenon of speedup anomalies in parallel search. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.