As construction projects get larger and more complicated, it becomes more difficult to make the final decision because of several factors such as cost, time, environment. Multi-objective optimization model provides a solution to this problem by making use of the Pareto front. This method can be used to assess multiple optimization objectives such as initial cost, maintenance cost, emission cost, etc. Subsequently, the most appropriate solution can be identified. It is implemented by following these steps [1]:
- identification of the problem
- identification of the optimization objectives
- developing the data structure
- standardization of the objectives
- definition of the fitness function
- establishment of the genetic algorithm.
Figure 1. General optimization procedure for maintenance scheduling [2]
The three parameters that we follow in this integration are costs, total intervention time and the distance between the interventions. The best options would have a maximized distance between the interventions and minimized cost and distance. The pareto front described by the total duration of the interventions and the cost is shown below:
Fig 2. Pareto Frontier – Duration, Distance and Cost
To see the accumulated impact of the input parameters on the performance criteria, duration and time gap between the interventions are visualised below. The red lines represent the optimal solutions while the blue lines represent the non-optimal solutions.
Fig 3. Accumulated Impact
Summary of approach:
REFERENCES
[1] Choongwan Koo, Taehoon Hong & Sangbum Kim (2015) An integrated multi-objective optimization model for solving the construction time-cost trade-off problem, Journal of Civil Engineering and Management, 21:3, 323-333, DOI: 10.3846/13923730.2013.802733
[2] Maintenance of Structures and Infrastructure Systems, Mohamed Soliman, A.M.ASCE* Dan M. Frangopol, Dist.M.ASCE†