Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/58138
Title: A Mathematical and Heuristic Approach for Scheduling Repetitive Projects in a Bi-Objective Single Crew Model
Authors: Mathew, J
Paul, B
Keywords: Complete enumeration technique;IGA-SCRP;Mathematical model;Genetic algorithm;Repetitive projects
Issue Date: Sep-2021
Publisher: NIScPR-CSIR, India
Abstract: Projects in which same type of works/activities gets repeated in different locations or sites are known as repetitive projects. In repetitive project businesses, selecting the best choice from distinctive crew options for each activity is a very difficult task for the decision makers. To find an optimum schedule with respect to different objectives like total project cost, total project duration etc. is of utmost importance for any project industry. In this study we consider a single crew model and develop a mathematical model which can give optimal solutions to the various objectives considered here, by satisfying different constraints like the work continuity of different resources in different units, fine amount to the lagging day of each activity in every location and precedence activities of the project. The proposed model is applied using a solver and validated by using complete enumeration technique. As in the case of any computationally complex problem, for problems of large size, a heuristic methodology is essential to obtain a good schedule, as solving of mathematical model is computationally difficult. So, here we also propose a new heuristic based methodology named as IGA-SCRP (Improved Genetic Algorithm for Single Crew Repetitive Projects). It is a modified genetic algorithm based methodology and its performance is compared with solutions acquired from the mathematical model. The outcome from the results shows that the proposed heuristic gives quality of solutions with minimal computational effort.
Page(s): 800-808
URI: http://nopr.niscair.res.in/handle/123456789/58138
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.80(09) [September 2021]

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