Bounded-Cost Bi-Objective Heuristic Search

There are many settings that extend the basic shortest path search problem. In Bounded-Cost Search, we are given a constant bound and the task is to find a solution within the bound. In Bi-Objective Search, each edge is associated with two costs (objectives) and the task is to minimize both objectives. In this paper, we combine both these settings into a new setting of Bounded-Cost Bi-Objective Search. We are given two bounds, one for each objective and the task is to find a solution within these bounds. We provide a scheme for normalizing the two objectives. We then introduce several algorithms for this new setting and compare them experimentally.

Authors

• Shawn Skyler
• Dor Atzmon
• Ariel Felner
• Oren Salzman
• Han Zhang 0018
• Sven Koenig
• William Yeoh 0001
• Carlos Hernández Ulloa

Keywords

• Problem Solving Using Search
• Combinatorial Optimization
• Analysis Of Search Algorithms
• Bounding And Pruning Techniques