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A heated stack based type-2 fuzzy multi-objective optimisation system for telecommunications capacity planning
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DOI：10.1016/j.knosys.2022.110134.png)
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Abstract
En 中文
In this paper, we present the Heated Stack Algorithm (HS) which is a population based multi-objective evolutionary algorithm with temperature based on type-2 fuzzy logic meta-heuristic. Temperature plays a vital role in HS being used for two distinct procedures; Sorting and Crossover. In sorting, temperature is combined with the niche distance to determine the rank order of a population front. In crossover, the temperature of two population members are compared to determine the quantity of information to take from each parent. HS is a new optimisation algorithm capable of solving constrained real-world problems. This paper will present the HS application to a real-world capacity planning problem involving networking infrastructure. To proof the algorithm applicability to wider set of problems, we will report the HS results over a subset of the constrained multi objective problems used for optimisation competitions by the IEEE Congress on Evolutionary Computation (CEEC). In these problems we have compared to the popular NSGA-II and its successor NSGA-III. By use of the hypervolume indicator, we find that the HS outperforms NSGA-II in 84% of cases, and outperforms NSGA-III in 69% of the cases. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Heated Stack
Optimisation
Fuzzy logic
Capacity Planning
Telecommunications
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