Multidisciplinary Optimization in Services Management

Abstract

Optimization methods may be applied to the services operations management. A comprehensive objective function (a cost-function to be minimized) leads to a multidisciplinary optimization, considering all aspects of a services business unit. However, this introduces a very large number of variables (examples with tens of thousands of variables are presented), making classical optimization methods inadequate. The paper introduces the use of genetic algorithms and illustrates it in two examples: air transport and leisure services. Multidisciplinary optimizations may play a crucial role in the success of any services business, and genetic algorithms are the most adequate computation resource in this type of optimizations.

Keywords

• multidisciplinary optimization
• services operating management
• genetic algorithms
• total costs and risks