Research On Collaborative Optimization Theory And Its Application For Project Payment Scheduling Under Leveling Optimization Of Resource

The issue of project investment payment scheduling is to study how to arrange activities reasonably considering the time value of capital so that both parties of the project implementation could maximize their economic interests. By optimizing project investment payment scheduling, the root of economic dispute exists between both parties could be eliminated. It is the most effective method to realize win-win. However, traditional investment payment scheduling only pursues static optimization in finance, which is an expected return before the implementation of the project. In fact, influences from other factors on scheduling are neglected, especially that of resource allocation. Since different types of scheduling lead to different distribution of resource demand, and cause different implementation costs, the practical interests of both parties will be influenced directly. Thus, it is clearly neither fair nor reasonable that only consider both parties’ return financially when dealing with the issue of payment scheduling. In the thesis, the influences from financial returns of both parties and resource allocation on project payment scheduling are considered collaboratively, and seek a balance between these two factors, and then find out a leveling point that is acceptable mutually. For that puipose, network resource leveling and collaborative optimization for investment payment scheduling are studied in this thesis. The specific contents are as follows:(1) Aiming at assumptions and defects of execution mode for activities and resource that traditional resource leveling algorithm has, practical executions of multi-modal activities and multiple resource allocation modes are analyzed, and a resource leveling optimization model for non-conventional resource allocation with multi-mode activities is constructed. A solution algorithm is also provided.(2) Risks and harms that translation strategy in traditional algorithm brings to the project are analyzed. An idea of allowing resource to be scheduled between a pair of activities is proposed. A leveling optimization strategy for activity translation and dynamic resource adjustment in activities is established, and a resource leveling optimization model and solution algorithm is also constructed under that strategy.(3) Specialties of Finish-to-Start precedence relation with zero time-lag between a pair of activities are analyzed. Several generalized precedence relations and their minimum time intervals are studied, and a resource leveling optimization model with generalized precedence relation and the solution algorithm are built.(4) The influence on project execution costs from imbalanced resource distribution is analyzed. The issue of investment payment scheduling in the condition of resource leveling is studied. Resource leveling and collaborative optimization of investment payment scheduling are considered comprehensively, and the associated multi-objective optimization model is built.(5) Network schedule optimization is the typical NP hard problem, and especially when the nature of accurate solution for large scale resource optimization goes worse, it is difficult to solute within effective calculation time. Thus, to show the practicality of the above leveling optimization model, and based on the achievements of SA in solving combinatorial optimization, a heuristic algorithm of improved SA which is approximate optimal solution is studied, including the SA with memory, the SA with going back and random seeking, the SA with random multiple optimization.