Optimization Model of Schedule-Non-Commercial Resources Provided by Employers of Large Project Programs. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Feng, Hui; Feng, Jingchun; Yang, Yanyan
• Is Part Of: Engineering management journal. Volume 34:Issue 2(2022)
• Page Start: 217
• Page End: 229
• Publication Date: 2022-04-03
• Subjects: South-North Water Transfer Project -- Resource Management Program -- Project Scheduling -- NCRPE -- Resource Optimization; Program & Project Management; Engineering -- Management -- Periodicals; Engineering -- Management; Periodicals; 620.0068
• DOI: 10.1080/10429247.2020.1861855
• Languages: English
• ISSNs: 1042-9247

Abstract

Abstract: Non-commercial resources provided by employers (NCRPE) are the imperative factors affecting the progress of engineering projects. However, the NCRPE with limited supply ability is rarely considered in the schedule optimization models in previous studies. The NCRPE schedule requirement may exceed its limitation, resulting in failing to optimize the schedule. Therefore, a new schedule optimization model is built from the perspective of NCRPE. First, the features of NCRPE and corresponding optimization theory are analyzed. Then, two optimization models are proposed in multi-contract environment before and during the construction of a project, aiming to minimize the unbalance coefficient, variance of NCRPE, and the requirement strength of NCRPE, respectively. Finally, a case study about the South-North Water Transfer Project Program X is conducted. The results show that the proposed model could effectively solve the NCRPE schedule optimization problem. A reasonable and practical program planning and adjustment within different stakeholders can be obtained. The NCRPE schedule optimization can minimize the peak demand amount of the program resources and achieve a relatively balanced total resource demand before the program implementation. Besides, it ensures that the original production system capacity can satisfy the actual demand in the program implementation. The research results can provide a basis for the bidding of each contracted project in the program and the resources optimization of each contracted project in the program implementation process.