A Hybrid-Based Framework for Constraint Satisfaction Optimization Problems

Scheduling and timetabling are commonly faced problems in most businesses and organizations. Both of these problems fall under the domain of constraint satisfaction optimization problems (CSOP), which involves finding a solution that satisfies all hard constraints, while at the same time maximizing some weighted sum of the soft constraints. Current constraint satisfaction techniques fare poorly in terms of soft constraints satisfied, while optimization techniques cannot ensure the feasibility of the final solution. In this paper, we propose a framework for CSOP that combines both constraint satisfaction and optimization techniques into a hybrid algorithm, called the combined method (CM). We test our framework on an exam-timetabling problem (ETTP) using actual data. Our results show that CM can be expected to produce better results than using a single technique alone.