Fuzzy multi-objective programming: A systematic literature review

Karimi, Negar; Feylizadeh, Mohammad Reza; Govindan, Kannan; Bagherpour, Morteza

doi:10.1016/j.eswa.2022.116663

Cited by 27 publications

(7 citation statements)

References 406 publications

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“…To select the final solution amongst the set of Pareto solutions created by the MOPSO, a linear fuzzy rule is utilized. This approach is commonly employed while no preference/priority between the objectives is considered [28]. Based on Equations ( 43…”

Section: Fuzzy-based Satisfaction Rulementioning

confidence: 99%

A Robust Renewable Energy Source-oriented Strategy for Smart Charging of Plug-in Electric Vehicles Considering Diverse Uncertainty Resources

Ahmadigorji

Mehrasa

2023

IJE

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Section: Fuzzy-based Satisfaction Rulementioning

confidence: 99%

A Robust Renewable Energy Source-oriented Strategy for Smart Charging of Plug-in Electric Vehicles Considering Diverse Uncertainty Resources

Ahmadigorji

Mehrasa

2023

IJE

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“…MOO is important because it can model real-world problems with multiple conflicting objectives [59,60]. To address the various challenges in the building energy sector, energy optimization applying MOO is essential to meet users' needs while also reducing technical issues and energy usage in the building energy sector.…”

Section: Energy Optimization In Buildingsmentioning

confidence: 99%

A Review of Methodologies for Managing Energy Flexibility Resources in Buildings

Pedram,

Asadi,

Chenari

et al. 2023

Energies

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The integration of renewable energy and flexible energy sources in buildings brings numerous benefits. However, the integration of new technologies has increased the complexity and despite the progress of optimization algorithms and technologies, new research challenges emerge. With the increasing availability of data and advanced modeling tools, stakeholders in the building sector are actively seeking a more comprehensive understanding of the implementation and potential benefits of energy optimization and an extensive up-to-date survey of optimization in the context of buildings and communities is missing in the literature. This study comprehensively reviews over 180 relevant publications on the management and optimization of energy flexibility resources in buildings. The primary objective was to examine and analyze prior research, with emphasis on the used methods, objectives, and scope. The method of content analysis was used to ensure a thorough examination of the existing literature on the subject. It was concluded that multi-objective optimization is crucial to enhance the utilization of flexible resources within individual buildings and communities. Moreover, the study successfully pinpointed key challenges and opportunities for future research, such as the need for accurate data, the complexity of the optimization process, and the potential trade-offs between different objectives.

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“…Currently, there are two types of numerical approaches for dealing with multi-objective problem (MOP): classical numerical methods and intelligent optimization algorithms (Karimi et al, 2022). In classical methods, a MOP is transformed into a single-objective problem (SOP), and then an exact or optimization algorithm is used to solve the problem.…”

Section: Solution Approach For Multi-objective Problemmentioning

confidence: 99%