Research On Resoure-constrained Project Scheduling For Outdoor Projects Considering Weather Conditions

A reasonable project schedule can reduce the cost and makespan,as well as improve robustness of the project.Common outdoor projects are susceptible to weather conditions,and the amount of resources is limited.According to the practical demand of manufacturers,this paper studies resource-constrained project scheduling problem for outdoor projects considering weather conditions,focusing on the construction and maintenance process of wind farms.The main research parts of this paper are explained as follows.Firstly,multi-project scheduling problem with time constraints is considered,and the aim is minimizing the resource cost and production loss.A mixed integer linear programming model is proposed,and the bio-objective problem is transferred into several single objective problems through the main object method.The results from the practical case study confirm that the resource cost and production loss obtained by the proposed method is much better than the results from the manual periodic plans,decreased by nearly 30% and 20%,respectively.Secondly,the randomness of activity durations is further considered.Then stochastic optimization model for resource-constrained project scheduling problem is studied with the time-dependent probability distribution model for activity durations.An improved estimation of distribution algorithm(EDA)including a ranking and selection method using the common random numbers is proposed to enhance the performance of project scheduling.Results from both the benchmark dataset J120 from PSPLIB and the practical case study of the wind farm construction project confirm that the improved EDA can identify better solutions more efficiently than the existing EDA.Finally,the coping strategy for disruptions incurred by the change of weather conditions and resource supply is investigated.Based on disruption management,the multi-mode project scheduling problem is studied,aiming at minimizing the cost from the deviation between the adjusted schedule and the original schedule.These disruptions are classified,and different recovery strategies are proposed.A rolling optimization model is then built and solved by Tabu Search.Results from both the benchmark dataset MM100 from PSPLIB and the practical case study of the wind farm construction show that the proposed method is effective and efficient.In conclusion,according to the requirements from the practical project,the meteorological changes are analyzed,and the estimation model of activity durations is constructed.A hybrid integer linear programming model for the multi-project scheduling problem is developed,and the efficiency and quality of simulation optimization are improved by rational allocation of simulation resources.Besides,the theory of disruption management is combined with reactive scheduling for outdoor projects.In addition,some of the research results have been applied in the management of enterprises and obtained considerable practical value and economic benefits.