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Research On Multi-resource Constrained Project Scheduling Problems Based On Genetic Algorithm

Posted on:2016-01-14Degree:MasterType:Thesis
Country:ChinaCandidate:J H XuFull Text:PDF
GTID:2309330464450451Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Project scheduling is an important part of project management in time scheduling with realistic meanings. Resource-constrained project scheduling problem(RCPSP) is a typical issue in project scheduling management. The objective is to schedule the activities subject to precedence relations and resource constrains in order to minimize the total project duration. The RCPSP is a kind of NP-hard(Non-deterministic polynomial-time hard) combination optimization problem, and this kind problem only needs the suboptimal solutions instead of the optimal solutions.This Paper summarizes the development of project scheduling and the solving method models. It is to study the RCPSP model after analyzing the differences of different project scheduling models. GA(Genetic Algorithm) has good effect in solving the RCPSP. In this paper, a new GA program is designed based on the characters of RCPSP. For example, a new two-point crossover operator, the elite strategy and local search algorithm are integrated in GA. The standard example of the Project Scheduling Problem Library(PSPLIB) is chosen to test the improved GA program, and also compare the performance of different algorithms. The results show the superiority of the improved genetic algorithm. Then an actual project scheduling case is introduced to test the model and algorithm.However, there is big deviation between the classical RCPSP model and the actual project scheduling, and one of the reasons is the uncertainty execution time of project activities. This paper introduces the fuzzy theory to describe the uncertain activity execution time and six-point fuzzy number is used to solve this problem. And the fuzzy example of PSPLIB is used to test the program. The fuzzy time RCPSP model and the improved GA program are applied in the actual case to further explain the practicability and feasibility of scheduling model and algorithm.
Keywords/Search Tags:Multi-resource constrained, Project scheduling, Genetic Algorithm, Fuzzy theory, Local search
PDF Full Text Request
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