This paper focus on artificial intelligence approaches to NP-hard job shop scheduling (JSS)
problem. In the literature successful approaches of artificial intelligence techniques such as …

Early and seminal work which applied evolutionary computing methods to scheduling
problems from 1985 onwards laid a strong and exciting foundation for the work which has …

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 …

In this paper we present a general genetic algorithm to address a wide variety of sequencing
and optimization problems including multiple machine scheduling, resource allocation, and …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

Silicon Second Nature takes us on an expedition into an extraordinary world where nature is
made of bits and bytes and life is born from sequences of zeroes and ones. Artificial Life is …

The job shop problem (JSP) is NP-hard, much harder than the traveling salesman problem.
This paper shows how a conventional Genetic Algorithm (GA) can efficiently solve the JSP …

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles
together with several significant monographs and books have been published on this …

Genetic algorithms have become increasingly popular as a means of solving hard
combinatorial optimization problems of the type familiar in operations research. This feature …