Nature-inspired algorithms for a scheduling problem in operational planning

Abstract

Abstract The scheduling problem is a widespread one, and it is still not automatized mostly because of the so-called combinatorial explosion. The paper describes two different approaches to solving a hierarchical scheduling problem based on solution representation. The first one proposes to find an optimal order of projects and then to solve the resource-constrained project scheduling problem for each of them. The second one assumes that we can find a priority of all activities for all projects and use it in the schedule building process if there is a conflict in the choosing of the next activity. The paper considers some nature-inspired algorithms such as the intelligent water drops algorithm, a genetic algorithm and ant colony optimization as well as a self-configuring version of the last two. The algorithm performance and different solution representation approaches are compared using the results of solving the test problems.