Comparisons of Linear Goal Programming Algorithms

Lack of an efficient algorithm capable of reaching a compromised solution within a reasonable time is a major setback in the use of goal programming. Orumie and Ebong newly developed an alternative method of solving goal programming problem utilizing modified simplex procedures. This algorithm is compared in terms of accuracy and time requirements with existing algorithms by Lee and by Ignizio. Computational times for 10 goal programming models of various sizes are presented. Number of iteration per problem, total entries per problems is used as benchmark for the comparisons. The new method by Orumie and Ebong (2011) have better  computational times in all the problem solution and proved the best since there is a reduction in computational time in all the problems solved. Keywords: Goal Programming, Lee’s modified simplex, Ignizio’s Sequential, Orumie and Ebong metho

An Efficient Method of Solving Lexicographic Linear Goal Programming Problem

Lexicographic Linear Goal programming within a pre-emptive priority structure has been one of the most widely used techniques considered in solving multiple objective problems. In the past several years, the modified simplex algorithm has been shown to be widely used and very accurate in computational formulation. Orumie and Ebong recently developed a generalized linear goal programming algorithm that is efficient. A new approach for solving lexicographic linear Goal programming problem is developed, together with an illustrative example. The method is efficient in reaching solution. Keywords: Lexicographic Goal programming, multi objective, simplex method

Comparisons of Linear Goal Programming Algorithms

Lack of an efficient algorithm capable of reaching a compromised solution within a reasonable time is a major setback in the use of goal programming. Orumie and Ebong newly developed an alternative method of solving goal programming problem utilizing modified simplex procedures. This algorithm is compared in terms of accuracy and time requirements with existing algorithms by Lee and by Ignizio. Computational times for 10 goal programming models of various sizes are presented. Number of iteration per problem, total entries per problems is used as benchmark for the comparisons. The new method by Orumie and Ebong (2011) have better  computational times in all the problem solution and proved the best since there is a reduction in computational time in all the problems solved. Keywords: Goal Programming, Lee’s modified simplex, Ignizio’s Sequential, Orumie and Ebong metho

Multivariate time series modeling of selected childhood diseases in Akwa Ibom State

This paper is focused on modeling the five most prevalent childhood diseases in Akwa Ibom State using a multivariate approach to time series. An aggregate of 78,839 reported cases of malaria, upper respiratory tract infection (URTI), Pneumonia, anaemia and tetanus were extracted from five randomly selected hospitals in the State from 1997 to 2011. The monthly Cumulative clinical cases of aforesaid childhood diseases constitute vector time series. Prewhitening approach was employed to determine whether the components of vector series are interrelated so that each series can be predicted on the bases of lagged values of itself and others. This process revealed that except tetanus; malaria, URTI, Pneumonia and anaemia series are interrelated. Hence, the four interrelated time series were considered in the multivariate analysis. Order selection criteria were employed to determine the order of the vector autoregressive (VAR) model to be fitted to these series. It was discovered that VAR(1) model fitted well. Diagnostic checks were applied to ascertain the adequacy of the model and VAR(1) model was found appropriate. Forecasts were generated. The model revealed that upper respiratory tract infection, pneumonia and anaemia are linked to or caused by malaria.Keywords: Multivariate Approach, Pre-whitening, Vector Time Series, Vector Autoregressive Model, Diagnostic Checks and Forecast