S.Lakshmi Narayanan | National Institute of Technology, Calicut (original) (raw)
Supervisors: Dr. Arun C
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Papers by S.Lakshmi Narayanan
Time, cost and risk in project delivery are amongst the crucial aspects of each project with both... more Time, cost and risk in project delivery are amongst the crucial aspects of each project with both client and contractor striving to optimize the project duration and cost concurrently. Studies have been conducted to model the time–cost relationships, ranging from heuristic methods and mathematical approaches to genetic algorithms. Emergence of new contracts that place an increasing pressure on maximizing the quality of projects while minimizing its time and cost, require the development of innovative models considering risk in addition to time and cost. In this research, a meta-heuristic multi-colony ant algorithm is developed for optimization of three objectives time-cost-risk as a trade-off problem. An attempt is made to develop a Multi Objective Optimization Model capable of minimizing time and cost of projects (inclusive of risk.
Time, cost and risk of project delivery are among the crucial aspects of each project with both c... more Time, cost and risk of project delivery are among the crucial aspects of each project with both client and contractor striving to optimize the project duration and cost concurrently. Studies have been conducted to model the time–cost relationships, ranging from heuristic methods and mathematical approaches to genetic algorithms. Emergence of new contracts that place an increasing pressure on maximizing the quality of projects while minimizing its time and cost, require the development of innovative models considering risk in addition to time and cost. In this research, a meta-heuristic multi-colony ant algorithm is developed for optimization of three objectives time-cost-risk as a trade-off problem. An attempt is made to develop a Multi Objective Optimisation Model (MOOM) capable of minimizing time and cost of projects (inclusive of risk) as multi-objective optimization of time-cost-risk. The model this developed is then compared with similar model and the efficiency of this model is ascertained. An example is analyzed to illustrate the capabilities of the present method in generating optimal/near optimal solutions. The result thus obtained from the algorithm developed is compared with solutions of the problem obtained from MAWA (modified adaptive weight approach) approach adopted by Feng et al. 1997 and MOACO (multi objective ant colony optimization) adopted by Afshar et al. 2006 and it is found that the model developed gives efficient results when compared to MAWA and comparable results when compared to MOACO.
Time, cost and risk in project delivery are amongst the crucial aspects of each project with both... more Time, cost and risk in project delivery are amongst the crucial aspects of each project with both client and contractor striving to optimize the project duration and cost concurrently. Studies have been conducted to model the time–cost relationships, ranging from heuristic methods and mathematical approaches to genetic algorithms. Emergence of new contracts that place an increasing pressure on maximizing the quality of projects while minimizing its time and cost, require the development of innovative models considering risk in addition to time and cost. In this research, a meta-heuristic multi-colony ant algorithm is developed for optimization of three objectives time-cost-risk as a trade-off problem. An attempt is made to develop a Multi Objective Optimization Model capable of minimizing time and cost of projects (inclusive of risk.
Time, cost and risk of project delivery are among the crucial aspects of each project with both c... more Time, cost and risk of project delivery are among the crucial aspects of each project with both client and contractor striving to optimize the project duration and cost concurrently. Studies have been conducted to model the time–cost relationships, ranging from heuristic methods and mathematical approaches to genetic algorithms. Emergence of new contracts that place an increasing pressure on maximizing the quality of projects while minimizing its time and cost, require the development of innovative models considering risk in addition to time and cost. In this research, a meta-heuristic multi-colony ant algorithm is developed for optimization of three objectives time-cost-risk as a trade-off problem. An attempt is made to develop a Multi Objective Optimisation Model (MOOM) capable of minimizing time and cost of projects (inclusive of risk) as multi-objective optimization of time-cost-risk. The model this developed is then compared with similar model and the efficiency of this model is ascertained. An example is analyzed to illustrate the capabilities of the present method in generating optimal/near optimal solutions. The result thus obtained from the algorithm developed is compared with solutions of the problem obtained from MAWA (modified adaptive weight approach) approach adopted by Feng et al. 1997 and MOACO (multi objective ant colony optimization) adopted by Afshar et al. 2006 and it is found that the model developed gives efficient results when compared to MAWA and comparable results when compared to MOACO.