Integrating random regret minimization-based discrete choice models with mixed integer linear programming for revenue optimization

Talebi, Amirreza; Haeri Boroujeni, Sayed Pedram; Razi, Abolfazl

doi:10.1007/s42044-024-00193-w

Iran J Comput Sci

2024

DOI: 10.1007/s42044-024-00193-w

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Integrating random regret minimization-based discrete choice models with mixed integer linear programming for revenue optimization

Amirreza Talebi,

Sayed Pedram Haeri Boroujeni,

Abolfazl Razi

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2024

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Cited by 2 publications

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Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

Madani,

Goodarzian,

Navaei

et al. 2024

Cent Eur J Oper Res

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Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

Madani,

Goodarzian,

Navaei

et al. 2024

Cent Eur J Oper Res

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Promoting Eco-Friendly Behavior in University Activity-Based Workspaces Through Eco-Feedback

Sadralashrafi,

Nahavandian,

Neyens

et al. 2024

Proceedings of the Human Factors and Ergonomics Society Annual

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Eco-feedback has been demonstrated as an effective strategy to promote energy-saving behavior among occupants in buildings by providing real-time or historical information on energy consumption and environmental impacts. However, the application of eco-feedback in academic buildings for space choices is limited. In this study, we explored the impact of providing eco-feedback on occupants’ space choices in university Activity-Based Workspaces (ABW), where individuals select their workspaces using an online booking system. We designed two user interfaces: one baseline interface with no eco-feedback, and also an intervention interface that included eco-feedback. A within-subject user interface evaluation study was conducted, and the results suggest that eco-feedback significantly motivates occupants to select highly eco-friendly spaces ( p-value < .05). Consequently, providing eco-feedback in university ABW environments can encourage more eco-friendly and sustainable decision making and has the potential to reduce the contribution of buildings in energy-related carbon emissions.

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Integrating random regret minimization-based discrete choice models with mixed integer linear programming for revenue optimization

Cited by 2 publications

References 37 publications

Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

Promoting Eco-Friendly Behavior in University Activity-Based Workspaces Through Eco-Feedback

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