Design of scheduling algorithms: Applications

This chapter discusses the insights developed for designing scheduling algorithms according to three design projects where algorithms have been developed. The choice of applications covers a broad spectrum. The methods used are from three different fields, namely combinatorial optimization, genetic (evolutionary) algorithms, and mathematical optimization. The application areas differ also in terms of the role of a human user of the algorithm. Some of these algorithms have been developed without detailed study of the competences of the perceived users. Others have examined humans when performing the scheduling tasks manually, but have not considered the change in cognitive load if the process of planning changes due to the new algorithm and computerized support. Although none of the design projects fulfils all criteria developed in the framework of Chap. 12, we show that the framework helps to assess the design projects and the resulting algorithms, and to identify the main weaknesses in these applications. Finally, we show how they can be addressed in future. The three application areas are: 1. Decision support for shunting yard scheduling using a network flow heuristic. 2. An evolutionary multi-objective decision tool for job-shop scheduling. 3. Group sequencing. A predictive-reactive scheduling method for job-shop scheduling.