Genetic algorithm scheduling: Difference between revisions

Revision as of 06:28, 30 June 2010

Revision as of 06:59, 19 September 2011

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{{IntroLead missing|date=September 2009}}

To be competitive, corporations must minimize inefficiencies and maximize productivity. In manufacturing, productivity is inherently linked to how well you can optimize the resources you have, reduce waste and increase efficiency. Finding the best way to maximize efficiency in a manufacturing process can be extremely complex. Even on simple projects, there are multiple inputs, multiple steps, many constraints and limited resources. In general a resource constrained scheduling problem consists of:

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==Bibliography==

* {{Citation

| last = Wall | first = M. | title = [A Genetic Algorithm for Resource-Constrained Scheduling | url = http://lancet.mit.edu/~mwall/phd/thesis/thesis.pdf A Genetic Algorithm for Resource-Constrained Scheduling] }}

* {{Citation

| last1 = Lim | first1 = C.

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* [[Quality control and genetic algorithms]]

* [[Genetic algorithm in economics]]

==External links==