Operations managers and scholars in their search for fast and good solutions to real-world
problems have applied genetic algorithms to many problems. While genetic algorithms are …

The emergence of GPU-CPU heterogeneous architectures has led to a fundamental
paradigm shift in parallel programming. Accelerating Genetic Algorithms (GAs) on these …

Traditional job shop scheduling is concentrated on centralized scheduling or semi-
distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and …

The first part of this chapter describes the foundation of genetic algorithms. It includes hybrid
genetic algorithms, adaptive genetic algorithms, and fuzzy logic controllers. After a short …

This paper proposes an improved hybrid genetic algorithm with variable neighborhood
search (HGA-VNS) for addressing the flexible job shop scheduling problem (FJSP) …

A comprehensive guide to a powerful new analytical tool by two of its foremost innovators
The past decade has witnessed many exciting advances in the use of genetic algorithms …

This paper proposes an effective new hybrid ant colony algorithm based on crossover and
mutation mechanism for no-wait flow shop scheduling with the criterion to minimize the …

Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic …

This paper presents a hybrid genetic algorithm for the job shop scheduling problem. The
chromosome representation of the problem is based on random keys. The schedules are …

The term 'Memetic Algorithms'[74](MAs) was introduced in the late 80s to denote a family of
metaheuristics that have as central theme the hybridization of different algorithmic …