Multi-objective Resource-constrained Project Scheduling Problem Ant Colony Algorithm

With the development of society and economy, project management has gradually become a popular topic both practically and theoretically. In recent years more and more scholars have donated themselves to the research of project scheduling, whichbelongs to the core aspect of project management------project planning. At thebeginning, the only factor considered in project scheduling is time. This makes the methods solving this kind of problems, such as critical path method and project evaluation and review technique, not suitable in management practice. Classic resource constrained project scheduling problem, due to its coincidence of actual project by considering the limit of different resources, has been well researched as many algorithms and heuristics have been developed and implied to RCPSP. However, currently there is very little research about multi-objective resource constrained project scheduling problem because of the complexity of the problem itself, although in the reality we often face similar situation: a project with more than one objective.In this research multi-objective resource constrained project scheduling problem with two objectives of total makespan and total weighted lateness is solved by using a kind of metaheuristic called ant colony algorithm which has been proved to be effective in combination optimization. It is the first time that ant colony optimization is used in solving multi-objective resource constrained project scheduling problems. Moreover, an improved multi-colony ant algorithm is developed and also proposed and implied to multi-objective resource constrained project scheduling problem. The effectiveness and efficiency of these two algorithms are tested by comparing the results of solving Patterson's 110 problems with some priority based heuristics. The computation result shows the advantage and fitness of the two kinds of ant colony algorithm in solving multi-objective resource constrained project scheduling problem as well as some drawbacks overcoming which can be the direction of future research in relative area.