Modeling and solving the project selection and scheduling

• This paper studies the integrated project selection and scheduling problem.
• Regarding shortcomings of available techniques, develops a mathematical model.
• It proposes an ant colony optimization.
• The algorithm is compared with two algorithms.

This paper considers the integrated bi-objective problem of projects selection and scheduling to optimize both total expected benefit and resource usage variation. The benefit is time-dependent. Although this integrated problem has become a very active field of research, the available model and algorithms suffer from serious shortcomings. This paper analyzes the available methods and develops a novel mathematical model, in form of a mixed integer linear program, for the problem. Then, it proposes an ant colony optimization algorithm employing four features of ant generation, colonial, Pareto front updating, and pheromone updating mechanisms. To evaluate the proposed algorithm, it is compared with two available genetic algorithm and scatter search. Using comprehensive numerical experiments and statistical tools, it is shown that the proposed ant colony optimization outperforms the two available algorithms.