Using metaheuristics-based methods to provide sustainable market solutions, suitable to consumer needs

• Autor(a) principal: Santos, Ricardo Simões
• Data de Publicação: 2020
• Outros Autores: da Costa Feliciano Abreu, António João Pina, Monteiro, Joaquim José Rodrigues
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/120411
• topic: Energy efficiency; Evolutionary Algorithms; Household Appliances; Multi-criteria; Multi-objective Optimization; Simplex; Sustainability; Engineering (miscellaneous); Physics and Astronomy (miscellaneous); Management of Technology and Innovation; SDG 7 - Affordable and Clean Energy

Nowadays the buildings sector is one of the key sectors to achieve sustainability, with the correspondent consumers, in particular, the household consumers, having the need to perform sustainable choices every day, regarding the appliances to be acquired from the market. This is not only due to government’s growing concerns about sustainability but also with the consumers on having sustainable solutions, given the different economic, social (including their comfort) and environmental needs. However, the existence of several electrical appliances on market, with all their different issues, brands and models, together with the several tradeoffs referred before, difficult the consumer’s choices, on having sustainable solutions in the market. Therefore, this work, presents an approach, by using Multi-Attribute Value Theory (MAVT), integrated with metaheuristics, which uses Evolutionary Algorithms (EA) to provide suitable and sustainable market solutions to a consumer, according to its own needs. Based on the achieved solutions and considering the relative importance, given to each consumer, and regarding each dimension of sustainability, it’s possible to achieve several savings, namely electrical and water consumption, CO2 emissions, among others. A case study shall be shown, to demonstrate the applicability of the proposed approach.