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R. Patel*, G. McKee* and T. Cornick#

*Department of Computer Science and #Department of Construction Management and Engineering, University of Reading, Reading, UK

doi:10.4203/ccp.35.4.1

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R. Patel, G. McKee, T. Cornick, "Rule based Inferencing for Project Staffing Schedules", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 45-49, 1995. doi:10.4203/ccp.35.4.1

Abstract

Conventional project management tools for the in-house design of civil engineering projects specify resource scheduling and planning at a high level, but do not specify detailed requirements such as a staffing schedule. A staffing schedule can be produced manually from the initial project plan, but as the project proceeds new information is acquired requiring task estimates of dates, durations, and effort, to be reviewed, resulting in a revised schedule. Maintaining consistency across tasks during this review process can be very complex and time consuming if performed manually. Artificial Intelligence (AI) techniques provide an effective means of change control management during this review process. This paper will describe an implementation which makes use of rule based inferencing to effect this change control.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 35 DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping Paper IV.1 Rule based Inferencing for Project Staffing Schedules R. Patel, G. McKee and T. Cornick# *Department of Computer Science and #Department of Construction Management and Engineering, University of Reading, Reading, UK doi:10.4203/ccp.35.4.1 purchase the full-text of this paper Full Bibliographic Reference for this paper R. Patel, G. McKee, T. Cornick, "Rule based Inferencing for Project Staffing Schedules", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 45-49, 1995. doi:10.4203/ccp.35.4.1 Abstract Conventional project management tools for the in-house design of civil engineering projects specify resource scheduling and planning at a high level, but do not specify detailed requirements such as a staffing schedule. A staffing schedule can be produced manually from the initial project plan, but as the project proceeds new information is acquired requiring task estimates of dates, durations, and effort, to be reviewed, resulting in a revised schedule. Maintaining consistency across tasks during this review process can be very complex and time consuming if performed manually. Artificial Intelligence (AI) techniques provide an effective means of change control management during this review process. This paper will describe an implementation which makes use of rule based inferencing to effect this change control. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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