Quantitative Analysis of an IPS2 Delivery Planning Approach

The delivery planning of Industrial Product-Service Systems (IPS2) is a complex task. A highly dynamic network of provider, customers and suppliers needs to be managed and coordinated. Due to this complexity, sophisticated IT-support for IPS2 resource planning is required. For this purpose, the adaptive IPS2 planning method (AIPM) for the scheduling of delivery processes has been conceptually developed in previous research. The method is based on a genetic algorithm, in which a population of planning solutions is evaluated with regard to a fitness value to identify the best plans. To be able to conduct quantitative evaluation studies on the effectiveness and efficiency of the planning algorithm, it has been implemented in a prototype of an IPS2-Execution System (IPS2-ES). It became apparent that some modifications of the algorithms were necessary in order to apply the approach to real planning cases. With these modifications, the algorithm was suitable to be used for further evaluation studies.In this paper, the results of these new evaluation studies with the modified algorithm are presented. A benchmarking problem set of the traveling salesman problem with time windows (TSPTW) and a real-life industrial planning setting were analyzed. The results show, that the revised version of the AIPM is capable of solving both problems satisfactorily. In particular, the planning outcomes in the industrial scenario indicate high potential for practical applications in service companies and IPS2 networks.