Add to ORKGA Genetic Algorithm (GA) is applied to an employee scheduling optimization problem with varied, competing objectives and thousands of employees. An indirect chromosome encoding is used with genetic operators based on general GAs [13] and Evolutionary Strategies [6]. Population fitness is determined via a weighted-objective function, featuring a Balance Factor that encourages or disregards equality among the objectives. Initial results are promising. 1
We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt dia...
Optimal machine scheduling in general is unlikly to be solved in polynomial time. In practice heuris...
In Job Shop Scheduling (JSS) problems, there are usually many conflicting objectives to consider, su...
For workplaces with a preference or need for staffing around the clock, employees commonly work in s...
Genetic algorithms were intensively investigated in various modifications and in combinations with o...
The goal of the Fourth Industrial Revolution is to develop smart factories that ensure flexibility a...
The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across ...
Workers at large plantation companies have various activities. These activities include caring for p...
Abstract:- Generating high-quality schedules for a rotating workforce is a critical task in all situ...
Production scheduling is a notoriously difficult problem. Manufacturing environments contain comple...
This research proposes a method to solve the adaptive, multi-objective job shop scheduling problem. ...
We describe applications of Genetic Algorithms (GAs) to the Job Shop Scheduling (JSS) problem. More ...
Abstract. This paper describes techniques that can be applied to large-scale real-life employee time...
Genetic Algorithm (GA) has been widely used for optimizing the flow shop scheduling problem due to i...
Time Scheduling System represents a subclass of scheduling problems that are hard to solve. Genetic ...
We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt dia...
Optimal machine scheduling in general is unlikly to be solved in polynomial time. In practice heuris...
In Job Shop Scheduling (JSS) problems, there are usually many conflicting objectives to consider, su...
For workplaces with a preference or need for staffing around the clock, employees commonly work in s...
Genetic algorithms were intensively investigated in various modifications and in combinations with o...
The goal of the Fourth Industrial Revolution is to develop smart factories that ensure flexibility a...
The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across ...
Workers at large plantation companies have various activities. These activities include caring for p...
Abstract:- Generating high-quality schedules for a rotating workforce is a critical task in all situ...
Production scheduling is a notoriously difficult problem. Manufacturing environments contain comple...
This research proposes a method to solve the adaptive, multi-objective job shop scheduling problem. ...
We describe applications of Genetic Algorithms (GAs) to the Job Shop Scheduling (JSS) problem. More ...
Abstract. This paper describes techniques that can be applied to large-scale real-life employee time...
Genetic Algorithm (GA) has been widely used for optimizing the flow shop scheduling problem due to i...
Time Scheduling System represents a subclass of scheduling problems that are hard to solve. Genetic ...
We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt dia...
Optimal machine scheduling in general is unlikly to be solved in polynomial time. In practice heuris...
In Job Shop Scheduling (JSS) problems, there are usually many conflicting objectives to consider, su...