A comparative study of modeling and solution approaches for the multi-mode resource-constrained discrete time-cost trade-off problem: Case study of an ERP implementation project

Cakir G., SUBULAN K., YILDIZ Ş. A., Hamzadayı A., Asilkefeli C.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.169, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 169
  • Publication Date: 2022
  • Doi Number: 10.1016/j.cie.2022.108201
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: Multi-mode resource-constrained discrete, time-cost tradeoff problem, Constraint programming, Integer-linear programming, Genetic algorithm, ERP implementation projects, HYBRID GENETIC ALGORITHM, SCHEDULING PROBLEM, MULTIPLE-MODES, OPTIMIZATION, EXTENSIONS, FLOW
  • Van Yüzüncü Yıl University Affiliated: Yes


Most knowledge-intensive industries, especially companies developing software engineering projects such as Enterprise Resource Planning (ERP) implementation projects, generally necessitate finding the optimal trade-off between the project duration and total usage cost of the renewable resource costs (e.g., human resource expertise costs). Therefore, the MRC-DTCTP, which integrates classical multi-mode resource-constrained project scheduling (MRCPSP) and discrete time-cost trade-off problems (DTCTP), can be seen as a more applicable problem since it better reflects the objectives and requirements of today's real-life software project applications. The MRC-DTCTP is a much more complex variant of the MRCPSP since it aims to minimize total direct/indirect costs of the resources simultaneously under a pre-specified project deadline. Based on this motivation, a new explicit integer-linear programming (ILP) model of the MRC-DTCTP was first developed based on the implicit non-linear programming model of Wuliang and Chengen (2009). Due to its NP-hard nature, we also proposed a constraint programming (CP) model that includes several search strategies to solve large-sized problem instances within reasonable computation time. In addition, a genetic algorithm (GA) approach in combination with a Modified Serial Schedule Generation scheme (SSGS) is implemented to make further comparisons on several benchmark instances, which are generated based on the existing MRCPSP data sets taken from the project scheduling problem library (PSPLIB) by considering additional problem characteristics. A comprehensive experimental study has shown that the proposed CP model and GA approach can provide superior results in shorter run times for large-sized benchmark instances. Finally, an international Enterprise Resource Planning (ERP) Software Company's real-life application is presented. The ERP projects generally necessitate finding the optimal trade-off between project makespan and human resource costs, making the MRC-DTCTP much more difficult than classical MRCPSPs & DTCTPs. For further analysis, time-cost trade-off curves under different human resource avail abilities and project deadlines are drawn to provide managerial insights to ERP project managers.