A Hybrid Framework for Over-Constrained Generalized

Abstract. In this work we study an over-constrained scheduling problem where constraints cannot be relaxed. This problem originates from a local defense agency where activities to be scheduled are strongly ranked in a priority scheme determined by planners ahead of time and operational real-time demands require solutions to be available almost immediately. A hybrid framework is used which is composed of two levels. A high-level component explores different orderings of activities by priorities using Tabu Search or Genetic Algorithm heuristics, while in a low-level component, constraint programming and minimal critical sets are used to resolve conflicts. Realdata used to test the algorithm show that a larger number of high priority activities are scheduled when compared to a CP-based system used currently. Further tests were performed using randomly generated data and results compared with CPLEX. The approach provided in this paper offers a framework for problems where all constraints a...

• Type: Journal
• Year: 2004
• Where: AIR
• Authors: Andrew Lim, Brian Rodrigues, Ramesh Thangarajo, Fei Xiao
• Keywords: AIR 2004, Genetic Algorithm Heuristics, Local Defense Agency, Over-constrained Scheduling Problem