Overall benefit-duration optimization and its genetic algorithim application in construction project scheduling

In this research, a new concept of Overall Benefit-Duration Optimization (OBDO) is proposed with objective function to maximize overall benefit of a construction project in scheduling process. An integrated solution model is developed by applying genetic algorithm and named as Genetic Algorithm Over...

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Bibliographic Details
Main Author: Pan, Heng
Other Authors: Ting Seng Kiong
Format: Theses and Dissertations
Language:English
Published: 2010
Subjects:
Online Access:https://hdl.handle.net/10356/41774
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Institution: Nanyang Technological University
Language: English
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Summary:In this research, a new concept of Overall Benefit-Duration Optimization (OBDO) is proposed with objective function to maximize overall benefit of a construction project in scheduling process. An integrated solution model is developed by applying genetic algorithm and named as Genetic Algorithm Overall Benefit-Duration Optimization (GAOBDO). In order to facilitate practical usage, GAOBDO is coded in VBA (Visual Basic for Application) macro program in Microsoft Project 2003 as an application platform, which automates data input, model structure and outcome interfaces. Given a normally-planned construction project with minimum cost, under a prerequisite that network compression-incurred opportunity income exceeds cost increment, it is lucrative to compress the project network to a desired duration where overall benefit, which refers to the difference between opportunity income and cost increment, is maximized. This problem is referred to as Overall Benefit-Duration Optimization (OBDO). Unlike time-cost trade-off problems that minimize cost, OBDO is a new scheduling optimization scheme for maximum overall benefit and prone to interests of a project owner. In addition, as a win-win solution, incentive fee is introduced in OBDO as an economic reward to contractor. As a combinatorial optimization problem, OBDO is complex and requires iterative selections of task crashing in network compression. Considering the number of possible iterations involved in this optimization process, optimal OBDO solution is difficult and time-consuming. Integrating extensive searching power of GA in combinatorial optimization problems, OBDO is modeled to maximize overall benefit and accounts for network compression-incurred influences to profitability of a construction project. After experimenting on various cases drawn from journal papers and real practice, 3 typical case studies of various-sized project networks are applied to demonstrate feasibility of OBDO concept and practicability of GAOBDO model.