<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We discuss the concept of simulation and its application in the resolution of problems in complex industrial systems. Most problems of serious scale, be it an inventory problem, a production and distribution problem, a management of resources or process improvement, all real world problems require a mix of generic, data algorithmic and Ad-hoc solutions making the best of available information. We describe two projects in which analytical solutions were applied or contemplated. The first case study uses linear programming in the optimal allocation of advertising resources by a major internet service provider. The second study, in a series of projects, analyses options for the expansion of the production and distribution network of mining products, as part of a sensitive strategic business review. Using the examples, we make the case for the need of simulation in complex industrial problems where analytical solutions may be attempted but where the size and complexity of the problem forces a Monte Carlo approach.</p></abstract>

We discuss the concept of simulation and its application in the resolution of problems in complex industrial systems. Most problems of serious scale, be it an inventory problem, a production and distribution problem, a management of resources or process improvement, all real world problems require a mix of generic, data algorithmic and Ad-hoc solutions making the best of available information. We describe two projects in which analytical solutions were applied or contemplated. The first case study uses linear programming in the optimal allocation of advertising resources by a major internet service provider. The second study, in a series of projects, analyses options for the expansion of the production and distribution network of mining products, as part of a sensitive strategic business review. Using the examples, we make the case for the need of simulation in complex industrial problems where analytical solutions may be attempted but where the size and complexity of the problem forces a Monte Carlo approach.

The need for simulation in complex industrial systems

University of Technology Sydney, School of Civil and Environmental Engineering,15 Broadway, Ultimo, NSW 2007, Australia

University of Maribor, Faculty of Organizational Sciences, Kidričeva 55a, Kranj, Slovenia

The George Washington University, Department of Physics, 805 21st Street, NW, Suite 301, Washington, DC 20052, U.S.A.

Organizacija

{"article-title":"The need for simulation in complex industrial systems"}

We discuss the concept of simulation and its application in the resolution of problems in complex industrial systems. Most problems of serious scale, be it an...

The need for simulation in complex industrial systems

Online veröffentlicht: 31. Okt. 2012

Seitenbereich: 219 - 227

DOI: https://doi.org/10.2478/v10051-012-0022-4

This content is open access.