Buku Genetic Algorithm in Supply Chain Optimisation

 
Penulis Ir. Muhammad Ridwan Andi Purnomo, S.T., M.Sc., Ph.D., IPM.
Institusi
Kategori Buku Referensi
Bidang Ilmu Teknik
ISBN 978-623-02-4223-6
Ukuran 15.5×23 cm
Halaman xii, 67 hlm
Ketersediaan Pesan Dulu
Tahun 2022
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Dikirim dari Sleman, Yogyakarta

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Sinopsis Buku Genetic Algorithm in Supply Chain Optimisation

Buku Genetic Algorithm in Supply Chain Optimisation

Genetic algorithm (GA) is one of the powerful searching algorithms that is widely applied in static and stochastic optimisations. In industrial engineering world, GA has also been applied for solving complex problems. One of the fields that is rapidly growing in industrial engineering is supply chain management. In terms of supply chain optimisation, it can be categorised into 2 optimisations, namely supply chain network configuration and lot size optimisation.

In its application, GA does not require complicated mathematical modelling that usually need a complicated algorithm to solve. Because of its simplicity, GA is widely used for system optimisation that is difficult to model using mathematical models. In term of the optimisation process, GA have numerous advantages over traditional optimisation algorithms. The ability to deal with complex problems and parallelism are two of the most utilised by previous researchers. GA can handle a wide range of optimisation problems, regardless of whether the objective function is static or stochastic, linear or nonlinear, and discrete or continuous. In GA, solution searching process is conducting by multiple chromosomes. Because the chromosomes in a population act independently, they can explore the search space in multiple directions at the same time. Because of this feature, it is ideal for parallelising algorithms for implementation.

This book consists of several chapters, namely: Chapter I Genetic Algorithm as Optimisation Tool, Chapter II Supply Chain Optimisation, Chapter III Application of Genetic Algorithms in Collaborative Supply Chain Optimisation, and Chapter IV Application of Genetic Algorithms in Supply Chain Lot Size Optimisation

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