An integrated selection and scheduling for large-sized disjunctive network problems

In network optimization problems, the application of conventional integrated selection and scheduling solution methods becomes complicated when the size of the problems, such as real life project management and transportation problems, get bigger. Additionally, the problems often consist of disjunctive networks, which traditionally results in separating the steps of the integrated approach. When the approach losses its integrated structure, the network problem also losses its integrity. To provide a new approach to maintain the problem integrity, we proposed an integrated genetic algorithm for solving this selection and scheduling problems together using a multistage decision approach. In this study, two example problems with different disjunctive networks and different characteristics have been solved using the proposed solution approach to highlight the performance and applicability to several other network optimization problems.