Study On Optimization Of Project Logistics Scheme Based On Decision Network Planning Technique

The project logistics is one part or whole-process of logistics service provided by logistics company, which services for project, such as equipment (production platform, large scale chemical industry equipment, generating set, etc.) stocking, installing, transiting, reclaiming. Different from common logistics, agent of project logistics is special equipment (ultra-large, ultra-long, over-weight, etc.). So the process of transportation and handling is with high difficulty and high risk. Because of these characteristics, the implementation process of such project logistics is uncertainty. The related design scheme must be more adaptive considering the uncertainty risk, which are resulted from the disposable procedure and complexity of such a project. The risk changes obviously when different schemes ( such as handling technology , location-routing) are chosen for one procedure. Thus, the differences of risk in the optimization of logistics scheme should be considered.Aimed at the above problem, PERT is used to express schemes in most studies, and functional relationship (such as time is inversely proportional to cost, quality is proportional to cost.) is established to connect parameters of procedure. But parameters of procedure in project logistics are changed with the choice of handling technology and location-routing and functional relationship of parameters is not obvious. Besides, the considering schemes are finite because of complex environment and practical conditions. So decision network planning is the best choice for optimization of logistics scheme. A decision unit structure including several discrete sample spaces, which is based on decision network planning technique, is presented. Stochastic programming theory is introduced in the optimization and an upper bound minimal model with consideration of both cost and risk is established. A case study is given to verify the effectiveness and practicability of the model. The result shows that the model can solve the optimization problem of project logistics scheme even when risks are different. And the present study is of highly theoretical significance and practical value.