A New Many-Objective Hybrid Method to Solve Scheduling Problems

This paper proposes a new hybrid method to solve extended scheduling problems that can include multiple resources, projects, and tasks with specific attributes, relationships, and constraints, as well as many objective functions with individual optimization directions and variable importance. A new decision-making procedure is proposed to combine metaheuristic search strategies, constructive algorithms, and many-objective comparison models. This paper also presents a concrete realization in which an advanced mixture search algorithm drives a flexible controllable constructive algorithm, and a relative qualification model ensures multi-objective optimization. Some numerical results illustrate the effectiveness of the proposed hybrid method.