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 been reported over the past decade or so. A survey of the current state-of-the-art was produced in 1999 for the European Network of Excellence on Evolutionary Computing EVONET¿this paper provides a more up-to-date overview of the area, reporting on current trends, achievements, and suggesting the way forward
The choice of a search algorithm can play a vital role in the success of a scheduling application. E...
Abstract Practical constraints associated with real-world problems are a key differentiator with res...
Evolving production scheduling heuristics is a challenging task because of the dynamic and complex p...
Early and seminal work which applied evolutionary computing methods to scheduling problems from 1985...
This article describes the genetic algorithm used to solve the problem related to the scheduling the...
This paper describes a Evolutionary Computation (EC) -based tool for the Job-shop Scheduling Proble...
The study of earliness and tardiness penalties in scheduling is a relatively recent area of research...
Practical constraints associated with real-world problems are a key differentiator with respect to m...
Scheduling is an active area of research in applied artificial intelligence. Scheduling problems typ...
Abstract:- Generating high-quality schedules for a rotating workforce is a critical task in all situ...
The paper is devoted to solution of multistage scheduling problems by genetic algorithms. The Heuris...
This chapter discusses the insights developed for designing scheduling algorithms according to three...
In every system, where the resources to be allocated to a given set of tasks are limited, one is f...
Over the past few years, a continually increasing number of research efforts have investigated the a...
The simultaneous advancement in genetic modeling and data computational capabilities has prompted pr...
The choice of a search algorithm can play a vital role in the success of a scheduling application. E...
Abstract Practical constraints associated with real-world problems are a key differentiator with res...
Evolving production scheduling heuristics is a challenging task because of the dynamic and complex p...
Early and seminal work which applied evolutionary computing methods to scheduling problems from 1985...
This article describes the genetic algorithm used to solve the problem related to the scheduling the...
This paper describes a Evolutionary Computation (EC) -based tool for the Job-shop Scheduling Proble...
The study of earliness and tardiness penalties in scheduling is a relatively recent area of research...
Practical constraints associated with real-world problems are a key differentiator with respect to m...
Scheduling is an active area of research in applied artificial intelligence. Scheduling problems typ...
Abstract:- Generating high-quality schedules for a rotating workforce is a critical task in all situ...
The paper is devoted to solution of multistage scheduling problems by genetic algorithms. The Heuris...
This chapter discusses the insights developed for designing scheduling algorithms according to three...
In every system, where the resources to be allocated to a given set of tasks are limited, one is f...
Over the past few years, a continually increasing number of research efforts have investigated the a...
The simultaneous advancement in genetic modeling and data computational capabilities has prompted pr...
The choice of a search algorithm can play a vital role in the success of a scheduling application. E...
Abstract Practical constraints associated with real-world problems are a key differentiator with res...
Evolving production scheduling heuristics is a challenging task because of the dynamic and complex p...