Applied Metaheuristic Computing

Format:

Book

Author/Creator:

Yin, Peng-Yeng, Editor.

Contributor:

Chang, Ray-I, Editor.

Gheraibia, Youcef, Editor.

Chuang, Ming-Chin, Editor.

Lin, Hua-Yi, Editor.

Lee, Jen-Chun, Editor.

Yin, Peng-Yeng

Chang, Ray-I

Gheraibia, Youcef

Chuang, Ming-Chin

Lin, Hua-Yi

Lee, Jen-Chun

Language:

English

Physical Description:

1 electronic resource (684 p.)

Place of Publication:

Basel MDPI - Multidisciplinary Digital Publishing Institute 2022

Language Note:

English

Summary:

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC.

ISBN:

3-0365-5570-6

Access Restriction:

Open access Unrestricted online access