Project Scheduling Problem For Product Development Under Dynamic Environment And Its Solution

With the development of market economy and the improvement of industrial technology level, manufacturing industry is also faced with intensified market competition situation. In the fierce market competition product complexity and the difficulty of development is rising. Enterprises must develop their new products with lower prices and higher quality within a shorter time. At the same time, more and more people take cognizance of the importance of product development process. Up to now, many optimization theories and methods of product development process management have been proposed. At present, project management and project scheduling problems are becoming more widespread in practice. But, there are many kinds of uncertainties in the practical project scheduling which make it in a dynamic environment. Considering the influence of uncertainties when generating the schedule is the key problem to bridge the gap between theory and practice.Using the relevant theoretical research achievement for references, the project scheduling problem for product development under dynamic environment is modeled and simulated and its intelligent algorithm is also studied, which provides a new research approach to project scheduling problem for product development under dynamic environment.Firstly, through the analysis of existing problems, the formal description of project scheduling problem for product development under dynamic environment is made up. The characteristics of project scheduling problem for product development under dynamic environment, including coupled characteristic, uncertain parameter characteristic and environment disruption characteristic, are introduced from qualitative and quantitative analysis. The solution strategy based on these characteristics is also revealed. Meanwhile, as the basis for project scheduling problem modeling, the task coupling problem is described and analyzed. And a mixed set of coupled iterative model is established. The implementation steps for model simulation are also showed.Secondly, three characteristics of project scheduling problem for product development under dynamic environment, including coupled characteristic, uncertain parameter characteristic and environment disruption characteristic, are deeply researched:(1) For the coupled characteristic of project scheduling problem, a model of multi-mode multi-project scheduling problem is proposed. In order to solve the shared resources competing problem between the parallel projects, ant colony's labor division is employed to establish a priority-scheduling model. The particle is encoded based on task's mode and list which meeting the timing relationship to solve the timing constraints and resources competing problem between the tasks within a project. According to these methods, an improved particle swarm optimization algorithm which is based on vector switching method and combined division of labor priority model is used to find out the optimum scheduling scheme. The method is applied to a numerical example and compared with other heuristic algorithms based on priority rules.(2) For the uncertain parameter characteristic of project scheduling problem, fuzzy set theory is used to represent the uncertainty of activity duration and a model of project scheduling problem based on fuzzy activity duration is proposed. The parallel scheduling scheme for general project scheduling is extended to this problem and the criteria for fuzzy time series is defined. The solution space will generate lots of redundancy solution because of fuzzy duration, so a chaotic particle swarm optimization algorithm with two-stage is proposed. The algorithm has more local search features and can construct solution space better. Finally, this method is applied to a case of project scheduling for product development to illustrate and compared with other algorithms.(3) For the environment disruption characteristic of project scheduling problem, a classification scheme for the different types of disruptions is proposed and the recovery strategies for these disruptions, including task mode alternative strategy and resource alternative strategy, are defined. Then, a disruption management model under dynamic environment is established based on recovery strategies. The problem is solved with a Memetic algorithm mixed by genetic algorithm and multi-domain simulated annealing algorithm based on self-adaption meta-Lamarchian learning strategy. Finally, to test the procedure, the multi-mode test package J20 and J30 in PSPLIB are solved and analyzed.Finally, the project scheduling of large crawler rotary drilling rig is successfully accomplished based on the theoretical research results above. The case study indicates that the proposed methods are feasible and effective.