<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>Scheduling manufacturing operations is a complicated decision making process. From the computational point of view, the scheduling problem is one of the most notoriously intractable NP-hard optimization problems. When the manufacturing system is not too large, the traditional methods for solving scheduling problem proposed in the literature are able to obtain the optimal solution within reasonable time. But its implementation would not be easy with conventional information systems. Therefore, many researchers have proposed methods with genetic algorithms to support scheduling in the manufacturing system. The genetic algorithm belongs to the category of artificial intelligence. It is a very effective algorithm to search for optimal or near-optimal solutions for an optimization problem. This paper contains a survey of recent developments in building genetic algorithms for the advanced scheduling. In addition, the author proposes a new approach to the distributed scheduling in industrial clusters which uses a modified genetic algorithm.</p></abstract>

Scheduling manufacturing operations is a complicated decision making process. From the computational point of view, the scheduling problem is one of the most notoriously intractable NP-hard optimization problems. When the manufacturing system is not too large, the traditional methods for solving scheduling problem proposed in the literature are able to obtain the optimal solution within reasonable time. But its implementation would not be easy with conventional information systems. Therefore, many researchers have proposed methods with genetic algorithms to support scheduling in the manufacturing system. The genetic algorithm belongs to the category of artificial intelligence. It is a very effective algorithm to search for optimal or near-optimal solutions for an optimization problem. This paper contains a survey of recent developments in building genetic algorithms for the advanced scheduling. In addition, the author proposes a new approach to the distributed scheduling in industrial clusters which uses a modified genetic algorithm.

Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems

Faculty of Management, Warsaw University of Technology, Warsaw, Poland

Foundations of Management

{"article-title":"Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems"}

Scheduling manufacturing operations is a complicated decision making process. From the computational point of view, the scheduling problem is one of the most...

Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems

Data publikacji: 20 mar 2012

Zakres stron: 7 - 26

DOI: https://doi.org/10.2478/v10238-012-0039-2

Słowa kluczowe
manufacturing system, scheduling, genetic algorithm, genetic algorithms for the advanced

This content is open access.

Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems

Data publikacji: 20 mar 2012

Zakres stron: 7 - 26

DOI: https://doi.org/10.2478/v10238-012-0039-2

Słowa kluczowemanufacturing system, scheduling, genetic algorithm, genetic algorithms for the advanced

This content is open access.

Słowa kluczowe
manufacturing system, scheduling, genetic algorithm, genetic algorithms for the advanced