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Constraint programming-based transformation approach for a mixed fuzzy-stochastic resource investment project scheduling problem

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SOFT COMPUTING 2022年第5期26卷 2523-2560页

作者： Subulan, Kemal Cakir, Gizem Dokuz Eylul Univ Fac Engn Dept Ind Engn Izmir Turkey Dokuz Eylul Univ Grad Sch Nat & Appl Sci Izmir Turkey

In fuzzy mathematical programming literature, most of the transformation approaches were mainly focused on integer linear programs (ILPs) with fuzzy parameters/variables. However, ILP-based solution approaches may be inadequate for solving large-scaled combinatorial fuzzy optimization problems, like project scheduling under mixed fuzzy-stochastic environments. Moreover, many real-life project scheduling applications may contain different types of uncertainties such as fuzziness, stochasticity, and dynamism simultaneously. Based on these motivations, this paper presents a novel constraint programming (CP)-based transformation approach for solving a multi-objective and multi-mode, fuzzy-stochastic resource investment project scheduling problem (FS-MRIPSP) which is a well-known NP-complete problem. In fact, the proposed approach mainly depends on a bound and decomposition principle which divides fuzzy components of the problem into the crisp middle, lower, and upper level problems. Thus, it reduces the problem dimension and does not need to use any standard fuzzy arithmetic and ranking operations directly. Furthermore, the stochastic nature of the problem is also taken into account by using a multi-scenario-based stochastic programming technique. Finally, a weighted additive fuzzy goal program is embedded into the proposed CP-based transformation approach to produce compromise fuzzy project schedules that trade-off between expected values of project makespan and total resource usage costs. To show the validity and practicality of the proposed approach, a real-life application is presented for the production-and-operations management module implementation process of an international Enterprise Resource Planning software company. The fuzzy-stochastic project schedules generated by the proposed CP-based approach are also compared to the results of a similar ILP-based method. Computational results have shown that the CP-based approach outperforms the ILP-based method in te

关键词： Resource investment project scheduling problem Constraint programming Fuzzy mathematical programs Scenario-based stochastic programs erp implementation projects

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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

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年第0期169卷

作者： Cakir, Gizem Subulan, Kemal Yildiz, Seyda Topaloglu Hamzadayi, Alper Asilkefeli, Ceren Dokuz Eylul Univ Grad Sch Nat & Appl Sci Izmir Turkey Dokuz Eylul Univ Fac Engn Dept Ind Engn Izmir Turkey Van Yuzuncu Yil Univ Dept Ind Engn Van Turkey

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

关键词： Multi-mode resource-constrained discrete time-cost tradeoff problem Constraint programming Integer-linear programming Genetic algorithm erp implementation projects

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