What does this research mean for the field?

A novel analytical framework for the linear Best-Worst Method derives a closed-form expression for weights, mathematically proving their uniqueness and eliminating the need for optimization software while demonstrating superior computational efficiency. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop an analytical closed-form framework for the linear Best-Worst Method that mathematically proves weight uniqueness and eliminates dependency on optimization software.

September 2, 2026IMA Journal of Management Mathematics

An Analytical Framework for the Linear Best-Worst Method

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Authors

HRHarshit M. Ratandhara MKMohit Kumar

Discussion

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Overview

Methodological study demonstrates closed-form weight derivation for the linear Best-Worst Method, highlighting software-independent efficiency in multi-criteria decision-making.

Key Points

To develop an analytical closed-form framework for the linear Best-Worst Method that mathematically proves weight uniqueness and eliminates dependency on optimization software.
Formulated closed-form analytical equations for decision criterion weights and calculated baseline consistency index values for the linear model.
Evaluated the mathematical framework across five numerical examples and computational experiments to assess runtime efficiency and data sensitivity.
Applied the framework to rank 18 drivers across Industry 4.0, circular economy, and sustainability categories within sustainable agri-food supply chains.
Provided a rigorous mathematical proof establishing the uniqueness of optimal weights in the linear Best-Worst Method without numerical optimization solvers.
Demonstrated lower data sensitivity and superior computational efficiency compared to standard software-based optimization methods.

Cite This Study

Ratandhara et al. (2026) studied this question.

synapsesocial.com/papers/6a97e2c5c562ede874ec720c https://doi.org/10.1093/imaman/dpag027

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September 2, 2026IMA Journal of Management Mathematics

An Analytical Framework for the Linear Best-Worst Method

View Full Paper

Ask AI

Bookmark

Authors

HRHarshit M. Ratandhara MKMohit Kumar

Discussion

Member takes

Overview

Methodological study demonstrates closed-form weight derivation for the linear Best-Worst Method, highlighting software-independent efficiency in multi-criteria decision-making.

Key Points

To develop an analytical closed-form framework for the linear Best-Worst Method that mathematically proves weight uniqueness and eliminates dependency on optimization software.
Formulated closed-form analytical equations for decision criterion weights and calculated baseline consistency index values for the linear model.
Evaluated the mathematical framework across five numerical examples and computational experiments to assess runtime efficiency and data sensitivity.
Applied the framework to rank 18 drivers across Industry 4.0, circular economy, and sustainability categories within sustainable agri-food supply chains.
Provided a rigorous mathematical proof establishing the uniqueness of optimal weights in the linear Best-Worst Method without numerical optimization solvers.
Demonstrated lower data sensitivity and superior computational efficiency compared to standard software-based optimization methods.

Cite This Study

Ratandhara et al. (2026) studied this question.

synapsesocial.com/papers/6a97e2c5c562ede874ec720c https://doi.org/10.1093/imaman/dpag027

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