Abstract
An efficient iterative heuristic algorithm has been used to implement Bellman-Zadeh solution to the problem of optimization under fuzzy constraints. In this paper, we analyze this algorithm, explain why it works, show that there are cases when this algorithm does not converge, and propose a modification that always converges.
This work was supported in part by US National Science Foundation grant HRD-1242122 (Cyber-ShARE Center).
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Kreinovich, V., Figueroa-García, J.C. (2018). Optimization Under Fuzzy Constraints: From a Heuristic Algorithm to an Algorithm that Always Converges. In: Figueroa-García, J., López-Santana, E., Rodriguez-Molano, J. (eds) Applied Computer Sciences in Engineering. WEA 2018. Communications in Computer and Information Science, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-00350-0_1
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DOI: https://doi.org/10.1007/978-3-030-00350-0_1
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