There are many different areas in which optimization can help businesses make measurable improvements in efficiency and profitability. Since these solutions have typically involved extensive costs and time to implement, only large businesses have been able to take advantage of the technology. These early adopters have enjoyed the first mover advantage.
There are many business processes which would make excellent candidates for optimization technology.
The following section gives examples of areas where optimization technologies have been sucessfully deployed.
Scheduling applications are probably the most prominent application of advanced optimization technology. Scheduling problems are a great fit because they often involve a limited set of resources with lots of constraints and business rules on how and when they can be deployed. There are often multiple, sometimes competing goals for profitability, smooth allocation of work and balanced resource utilization.
Manufacturing scheduling, or job shop scheduling is similar to resource scheduling but is typically aimed at determining the order and timing of job runs on a set of fixed resources (machinery).
There are several companies who provide routing solutions for mixed fleets. Evolutionary algorithms enable you to route fleets with respect to additional business goals and constraints typically not supported by applications looking for shortest route or lowest cost solutions.
Engineering problems involving many decision variables or simulations are a good fit for evolutionary optimization. These problems are often non-linear in nature and thus a natural fit for non-mathematical optimization approaches.
Strategic project planning
Budgeting and planning for resource allocation among various initatives presents an interesting challenge for larger organizations. Optimization technology can help sort through all the go/no-go decisions, levels of funding and resource allocation decisions while evaluating the overall plan with respect to strategic goals.