Study On The Optimization Methods For Solving Multi-skill Personnel Constrained Product Development Project Scheduling Problem

With the rapid development of the market economy and the growing trend of economic globalization,the market competition pressure faced by enterprises is increasing.The fierce market competition has prompted enterprises to pay more attention to the product development process.By using project management technology,the company will rationally dispatch and allocate project tasks and resources,and strive to develop new products with higher quality in the shortest time and lowest cost.In the product development project scheduling,due to the increase in the number of tasks and the existence of multi-skilled development staff,the feasible solutions in task scheduling and staffing problems have increased dramatically.Therefore,how to optimize the schemes of multiple goals such as time and cost in the feasible feasible domain becomes a decision-making problem faced by enterprise project managers.In this paper,based on the background of software development industry and the research results at home and abroad,the multi-objective product development project scheduling problem with multi-skilled personnel constraints is modeled,and the intelligent optimization algorithms for solving this problem is studied.Then the standard numerical examples are used to simulate the simulation of the proposed algorithms,and the effectiveness of the algorithms is verified.Finally,the practicality of the research theory and methods is verified by the software product development practice case.The research results of this paper mainly include the following aspects:Firstly,this paper analyzes the problem of product development project scheduling under the constraints of multi-skilled personnel,and represents it as a multi-skill resource-constrained project scheduling problem.Then the constraints and optimization objectives of the multi-skill resource-constrained project scheduling problem studied in this paper are introduced in detail.Finally,the multi-objective multi-skill resource-constrained project scheduling problem is formulated,and the mathematical model is established.Secondly,this paper studies the solution approaches for solving the multi-objective and multi-skill resource-constrained project scheduling problem,and proposes two new intelligent optimization algorithms: 1)Based on the traditional multi-objective fruit fly optimization algorithm,the key operator is improved and the concept of fuzzy dominance is introduced.Then,a fruit fly optimization algorithm based on fuzzy dominance sorting is designed.2)In order to verify whether the intelligent optimization algorithm combined with the reinforcement learning mechanism can show good performance when solving complex problems.Based on the fuzzy dominance fruit fly optimization algorithm,this paper uses Sarsa-learning mechanism to control the evolution of the algorithm to improve the search efficiency of the algorithm.Then,a fuzzy-dominated fruit fly optimization algorithm based on Sarsa-learning is proposed.Thirdly,this paper uses two representative algorithms in the existing research as comparison objects to verify the effectiveness of the proposed algorithm.Then,standard numerical cases were solved using all algorithms,and the experimental results were statistically analyzed.The results show that,compared with the other algorithms,the proposed algorithms has good performance in terms of HyperVolume,Mean Ideal Distance and CPU running time etc metrics.Finally,in the above theory and research methods,this paper illustrates the practicability of the proposed methods of this paper through an example of product development project of AR-based locomotive product thread assembly management platform.