Modeling uncertainty in linear programming

Proposes a decision making under uncertainty approach for treating linear programming under uncertainty. The author formulates a payoff matrix for the linear program and then apply the usual decision analysis criteria. Also, the problems encountered in converting a linear program under uncertainty to one under ris

Modeling uncertainty in linear programming

Proposes a decision making under uncertainty approach for treating linear programming under uncertainty. The author formulates a payoff matrix for the linear program and then apply the usual decision analysis criteria. Also, the problems encountered in converting a linear program under uncertainty to one under ris

ePublishing: Challenges & Opportunities

The recent explosive development in information technology (IT) is challenging the traditional forms of communication and publishing. The new IT tools open a new kind of research practice that is impossible several years back. Journal publication is at a crossroad. Academics and Publishing houses have tough choices to make: either leave the journal system as is and face possible erosions or adopt and exploit the opportunities IT is providing. It seems academics are adopting the latter choice. Many publishers are adopting e-publication and more adopting the parallel publishing. However switching from traditional to electronic publishing raises a number of opportunities and challenges to the journal systems. The opportunities are: ease of access, fast response to authors, cost savings, large storage capabilities, fluidity of electronic document etc. Challenges include: Quality control of published material, preserving the peer review system, preserving the Intellectual property. The purpose of this paper is to review experiences in electronic journal publication and examine the opportunities and challenges facing the journal system. It will also attempt to set requirements and standards for e-journal publication

A MATHEMATICAL OPTIMIZATION MODEL FOR CHEMICAL PRODUCTION AT SAUDI-ARABIA FERTILIZER COMPANY

This paper develops a mathematical economic optimization model for chemical production at Saudi Arabian Fertilizer Company (SAFCO) for two of their major products, ammonia and urea.The amount of ammonia and urea produced is determined by the product reactor setting.A reactor setting is determined by a set of operating parameters, such as raw material feed rate, reactor air flow velocity, and pressure.The model selects the minimum cost operating strategy while meeting a given production target.A zero-one integer programming model is developed for each product.The relevant data for the model are obtained, and then the model is solved.The results of the model showed substantial savings per year in both ammonia and urea plants.A systmatic sensitivity analysis is conducted on the optimal solutions of the model.It is concluded that such models should be applied across the petrochemical industry plants in Saudi Arabia

Impact Of Inspection Errors On The Performance Measures Of A General: Repeat Inspection Plan

Multi-characteristic critical components exist in many systems. Such components may be a part of an aircraft, spac shuttle or a gas ignition system. An inspection plan for such components has been proposed in quality control tat deals with several types of classification errors made by the inspector. In this paper, performance measures for this plan are defined and the statistical and economic impact of the several types of inspection errors on these measures is investigated. The impact of the errors is studied by conducting sensitivity analysis on the errors utilizing computer software which implements an algorithm that determines the optimal parameters of the model of the plan. The behaviour of the performance measures upon variation in the levels of errors is investigated. The results indicate that these errors have a considerable effect on the performance measures of the inspection plan

Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function

In this paper, a fuzzy based process targeting model is developed for a product with multi-characteristic. It is assumed that the desired quality characteristics cannot be measured directly and has to be calculated indirectly from multi-input process parameters. A fuzzy relation between observed/input parameters and required/output characteristics is proposed. A genetic algorithm is developed to obtain optimal process targets. The utility of the proposed model and algorithm is illustrated by a realistic example

An Extreme Point Algorithm For A Local Minimum Solution To The Quadratic Assignment Problem

In this paper the network structure of basic solutions to the quadratic assignment problem (QAP) is revisited. The concept of a relative local star minimum is introduced. Results characterizing a relative local star minimum are obtained. Then an extreme point algorithm for QAP is proposed