Multi-objective optimization for the sustainability of infrastructure projects under the influence of climate change

Zhang, Yan; Chouinard, Luc; Power, Gabriel J.; Sasai, Kotaro; Bah, Abdoul Salam

doi:10.1080/23789689.2023.2171197

Cited by 3 publications

(1 citation statement)

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“…Frontiers in Built Environment frontiersin.org of problems addressed and finally metaheuristics for seeking the solution space to complex problems. For example, Joshi et al (2023) predicted the compressive strength of high-performance concrete and fibre-reinforced high-strength self-compacting concrete by the hybridization of the standard sparrow search algorithm and rock hyraxes swarm optimization, respectively. Dealing with the sources of uncertainties associated with the physical state of the infrastructure, climate change, and the economy, Zhang et al ( 2023) made a flexible decision-analysis tool for managers based on both multi-objective particle swarm optimization (MOPSO) and a non-dominated sorting genetic algorithm II (NSGA-II).…”

Section: Cost Control and Delay Uncertaintiesmentioning

confidence: 99%

A heuristic approach of modelling developing countries' construction sector uncertainties to improve the building environment

Pettang Nana,

Fandjio Yonzou,

Mbiada Mbiada

et al. 2024

Front. Built Environ.

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The building environment is predominated almost everywhere in developing countries by fuzzy and unconventional mechanisms, which forms the so-called “informal sector.” The implementation of projects by the owners themselves, small and medium-sized enterprises, in this environment requires severe cost control and time delivery. The construction process in such a complex area is subject to labour fluctuations, productivity variability, difficulties in logistic supply, poor management, use of unsuitable methods, instability of financial means, and therefore delays in the payment of accounts by the contracting authorities. The factors mentioned above are source of major discrepancies between the forecast costs, quality, and deadlines and those obtained at the end of the project. This explains the losses in the execution phase and the prejudices suffered by the main actors in the unconventional construction industry at all levels. By comparing this specific construction sector with the standards, specific uncertainties emerge at several levels of understanding and execution, which, for each task, are the variabilities in quantity, performance, and qualification of workers; the quality and cost fluctuations among supplying networks of materials; the availability and/or inadequacy of equipment used; and the improvised managerial and financial mechanisms. This study, based on matrix modelling of the components of the construction site, leads to implementation of a heuristic approach for assessing those construction costs and delays uncertainties. We proposed analytic formulations of uncertainties that are computed every iteration of possible scenarios. By adapting and applying an iterative (TABU Search), a heuristic algorithm for minimising costs and lead times, it is possible to combine virtually all the possible choices for the different variables in order to anticipate the impact and guide the decision-maker towards the scenario with the least uncertainty and a good reliability of occurrence. Considering the complex parameters of this site of “informal” construction, the model aims to enable stakeholders in the construction sector to incorporate uncertainties into their forecasts before taking decisions not only to reduce or decrease financial losses but also to increase their credibility and ultimately improve this common practice of sustainable construction.

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Section: Cost Control and Delay Uncertaintiesmentioning

confidence: 99%