Genetic algorithm-based decision support for the restoration budget allocation of historical buildings

Decision support approach based on multiple objectives and resources for assessing the relocation plan of dangerous hillside aggregations

“…For instance, in the assessment of building redevelopment, technical issues, such as the function and physical conditions, will be the major concerns (Perng et al, 2007). In aggregation relocation, consideration of assessment of current environment quality satisfaction, building physical conditions, and functional comfort are important.…”

Decision-Making Model Supporting the Process of Planning Expenditures for Residential Building Renovation

“…They are based on expert systems (Borissova, Mustakerov 2012) and AI (Artificial Intelligence) methods utilising fuzzy sets (Bucoń, Sobotka 2015), neural networks, evolutionary algorithms, etc. (Juan et al 2009;Perng et al 2007). The examples of other DSS systems based on the stochastic approach include: BMDSS (Building Maintenance Decision Support System) developed by Langevine et al (2006) and BELCAM (Building Envelope Life Cycle Asset Management) developed by Lounis and Vanier (2000).…”

Systematic budget allocation for transportation construction projects: a case in Taiwan

“…Fuzzy MCDM has also been applied to transportation development, such as the ranking of road investments by Pearman et al (1989), the assessment of the influence of highway constructions with AHP by Azis (1990), and the selection of constructors or procurement methods (Fong and Choi 2000;Al-Subhi Al-Harbi 2001;Mahdi et al 2002). Its applications to budget allocation include a mixed integer knapsack model for allocating funds to highway safety improvements by Emanuel and Kozanidis (2002), budget allocations with the Target Planning Model for academic organizations by Kwak and Diminnie (1987), resource allocation with the AHP by Ramanathan and Ganesh (1995), the use of a genetic algorithm to resolve budget allocation issues for historical site renovations by Perng et al (2007), the use of a non-linear planning model to process the optimal financial budgets of software development projects by Han et al (2005), and the use of multi-attribute utility theory to allocate budgets for infrastructure renewal projects in universities by Karydas and Gifun (2006). These research studies have produced good results in the selection or ranking of projects with fuzzy MCDM to tackle unquantifiable or qualitative issues, apart from budget allocations.…”