A Soft Computing Framework to Support Consumers in Obtaining Sustainable Appliances from the Market

Abstract

Currently, sustainability is considered a priority by society, with the household appliances being one of the economic sectors involved in achieving sustainability. However, the existence of several issues (e.g., energy and water consumption, reliability, initial cost, and illuminance, among others) together with the diversity of brands and models on the market, make the consumer’s decisions regarding sustainable options difficult, according to their concerns and related to each sustainability dimension (economic, environmental, and social). By combining evolutionary algorithms (EA) with multicriteria techniques, it is possible to achieve sustainable solutions for the consumer based on their requirements. In this paper, a method is presented to support the consumer by obtaining a set of sustainable household appliances on the market that suit their preferences, concerns, and needs. By using a case study to apply the approach developed here, a set of sustainable appliances from the market is obtained, where several benefits are achieved (e.g., energy and water consumption savings, avoidance of CO2 emissions) during the lifecycle of each appliance, chosen from the appliance’s industry.

Keywords

• sustainability
• energy efficiency
• cyberphysical system
• decision support systems
• lifecycle cost analysis (LCCA)
• multi-attribute value theory (MAVT)