An Evolutionary Approach for Project Organization Design: Producing Human-Competitive Results using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@PhdThesis{KHosraviani_2005,

• author = "Bijan KHosraviani",
• title = "An Evolutionary Approach for Project Organization Design: Producing Human-Competitive Results using Genetic Programming",
• school = "Department of Civil and Environmental Engineering, Stanford University",
• year = "2005",
• address = "USA",
• month = dec,
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-542-43149-4",
• language = "English",
• URL = "https://gpc.stanford.edu/publications/evolutionary-approach-project-organization-design-producing-human-competitive-results",
• URL = "http://crgp.stanford.edu/publications/dissertations/KHosraviani_2005.pdf",
• URL = "https://www.proquest.com/dissertations-theses/evolutionary-approach-project-organization-design/docview/304982197/se-2",
• size = "141 pages",
• abstract = "In the complex and rapidly changing business environment of the early 21st century, designing an effective and optimised organisation for a major project is a daunting challenge. Project managers have to rely on their experience and/or trial and error to come up with organisational designs that fit their particular projects. Painful and costly experience in a wide range of governmental and private organisations has demonstrated that projects to develop buildings, software and other products often fail, not because the design of individual components was at fault, but rather because the organisation performing the complex supervision and coordination tasks required for system integration failed due to information overload.

  The Virtual Design Team (VDT) simulation system, based on the information processing theories of organization science, was a successful attempt to develop an analysis tool for project organization design (Jin and Levitt, 1996). However, like the analysis tools that support many other design processes, VDT has no inherent ability to improve or optimize current designs automatically. It simply predicts performance outcomes ? in terms of time, cost and several measures of process quality ? for a particular project organization design alternative. A VDT user must thus experiment in {"}What if?{"} mode with different design alternatives in an attempt to find better solutions that can mitigate the identified risks for a given project configuration. The problem has many degrees of freedom, so the search space for better solutions is vast. Exploring this space manually is infeasible. VDT relies on the expertise of the human user, guided simply by intuition about ways to improve on prior designs, to find better solutions. So it offers no guarantee of optimality.",

• abstract = "Our research extends the capabilities of VDT and other similar organizational analysis tools by going beyond computer support for {"}What-if?{"} analysis to automated design of project organizations. Evolutionary computing methods such as genetic programming are used to design and develop a postprocessor for VDT to help project managers find near-optimal designs for their project organisations.

  This dissertation describes in detail the approach I developed to represent project organisation design alternatives in a genetic programming format, so that the design can effectively evolve. In addition, it demonstrates how I was able to represent different project performance objectives and constraints in a fitness function which can successfully guide the model toward searching for better designs.

  A preliminary version of my postprocessor optimiser beats the best human trial-and-error solutions developed by more than 40 teams over the past eight years. The postprocessor was awarded a Silver Medal for human-competitive results in genetic and evolutionary computation at the GECCO-2004 Conference.",

• abstract = "I discuss why I chose the evolutionary computing approach as opposed to classical optimisation methodology, and show some of the advantages and limitations of the evolutionary approach. There was no formal theory of project organisation design nor any analysis tools for predicting the performance of project organisations prior to the development of VDT in the 1990s. Not surprisingly, therefore, research by C.B. Tatum in the early 1980s found that current human-developed project organisation structures are the result of {"}natural{"} trial-and-error evolutionary processes. By applying the evolutionary computing approach to organisation design, my model is thus actually mimicking the nature of human organisation design. In addition, I demonstrate how my approach can create a powerful Human-Computer Interaction (HCI) environment that can motivate humans to think {"}outside the box{"} when designing project organisations.

  Using a combination of {"}intellective{"} (theorem proving) and {"}emulation{"} (natural, empirical) experiments, I validate the postprocessor's {"}near-optimal{"} solutions against findings of organisational contingency theory and human-derived solutions for a set of real test cases. By showing that {"}optimal{"} structure depends on the relative emphasis of time, cost and process quality outcome metrics, I extend contingency theory to develop a richer {"}micro-contingency theory{"} for project organisations.

  This research represents a significant step towards closing the relevance gap between organisation theory and organisation practice by addressing the issues of organisational design prescriptively. I analyse alternatives in terms of fitness functions that evaluate specific designs for {"}survival{"} and {"}reproduction{"} in the spirit of contingency theory. Finally, the thesis concludes with a summary of the contributions of this research in the three areas of organisation science, project management, and computer science.",

• notes = "ProQuest 3197452",

}

Genetic Programming entries for Bijan KHosraviani

Citations