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Utilizing RISKOptimizer to manage quality performance

Roy L. Nersesian (Roy L. Nersesian is an Associate Professor in the Department of Management and Marketing, School of Business Administration, Monmouth University, New Jersey, USA.)
Marvin D. Troutt (Marvin D. Troutt is Director, Center for Information Sciences and G. Jay Weinroth is Chairperson, Administrative Sciences, both at the College of Business Administration, Kent State University, Kent, Ohio, USA.)
G. Jay Weinroth (G. Jay Weinroth is Chairperson, Administrative Sciences, both at the College of Business Administration, Kent State University, Kent, Ohio, USA.)

Logistics Information Management

ISSN: 0957-6053

Article publication date: 1 August 2001

506

Abstract

New software products are now available that offer solutions to operational problems that could not be handled by traditional linear programming. The problem of quality performance described could previously only have been handled by writing a special purpose simulation program. Now it can be solved in a spreadsheet environment using Evolver and RISKOptimizer software. Evolver can identify a global rather than a local optimal solution when non‐linear relationships are present. RISKOptimizer takes the process one step further. It combines @RISK simulation capablity with Evolver’s optimization algorithms to handle stochastic variables (uncertain demand and prices).

Keywords

Citation

Nersesian, R.L., Troutt, M.D. and Weinroth, G.J. (2001), "Utilizing RISKOptimizer to manage quality performance", Logistics Information Management, Vol. 14 No. 3, pp. 196-200. https://doi.org/10.1108/09576050110390220

Publisher

:

MCB UP Ltd

Copyright © 2001, MCB UP Limited

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