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- W4367291427 abstract "Nature-inspired algorithms are inspired by the assorted processes that are realized in nature. These approaches are divided into different categories like swarm-based optimization approaches, evolutionary approaches, physical-inspired approaches, bio-inspired approaches, and so on. Swarm intelligence techniques are a collective behavior of a decentralized or self-organized system. These systems consist of numerous individuals with limited intelligence interacting with each other. Teaching–learning-based optimization (TLBO) technique could be a populace-based meta-heuristic technique made up of two phases, namely, teacher phase and learner phase. This algorithm depicts the classroom teaching methodology. After the inception of TLBO, several researchers have been continuously working to refine the performance of the algorithm. This article also permits an hybridized TLBO algorithm for a class of vehicle routing problem. A new phase inspired from elephant herding optimization (EHO) is incorporated with TLBO. The hybridized algorithm is entitled as hybridized teaching–learning-based optimization algorithm. The modified algorithm is applied to clarify a class of capacitated vehicle routing problem. The captured results validate the authenticity of the proposed technique." @default.
- W4367291427 created "2023-04-29" @default.
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- W4367291427 date "2023-01-01" @default.
- W4367291427 modified "2023-10-14" @default.
- W4367291427 title "A Hybridized Teaching–Learning-Based Optimization Algorithm to Solve Capacitated Vehicle Routing Problem" @default.
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- W4367291427 doi "https://doi.org/10.1007/978-981-19-7892-0_42" @default.
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