S. Sarifah Radiah Shariff

Dynamic conditional location allocation model for healthcare facilities

In order to maintain the effectiveness of healthcare delivery, the location of the facilities providing the service to the public is very crucial. It is to ensure that the chosen location network and its demand allocation serve the purpose of minimising social cost or equivalently maximising the benefits of the people. This study will accommodate the changes of demand in time, the need to upgrade the network capacity and the condition of existing facilities into a dynamic conditional location allocation model. Using the new model, a case study is presented.

Location Routing Inventory Problem with Transshipment Points Using p-Center

Location Routing Inventory Problem with Transshipment (LRIP-T) is a collaboration of the three components in the supply chain which are location-allocation, vehicle routing and inventory management problems that allows transshipment process, in a way that the total system cost and the total operational time are minimized. This study is to determine a set of customer points to act as the transshipment point as and when it is necessary, based on the surplus quantities it has, the quantities to ship to the needing customers and the sequence in which customers are replenished by homogeneous fleet of vehicles. This LRIP-T is modified by making one or more of the customer points in the distribution system as the transshipment points with the selection of the points are done using p-center. Sensitivity analysis for two cases: 1) unlimited supply, 2) limited supply are presented. Results show important savings achieved when compared to the existing model in solving the supply chain problem.

An alternative heuristic for capacitated p-median problem (CPMP)

The p-median (PMP) has the objective of minimizing total distance, a customer/patient needs to travel in order to get a service. Various algorithms have been developed to solve the problem and in this paper, an alternative approach of Genetic Algorithm based heuristics is used to solve the problem in minimizing the travelled distance for a patient to get healthcare service. Combination of the nearly-optimal number of facilities to open and the random node order assignment is used to minimize the average traveled distance. The approach is used to solve a capacitated PMP (or CPMP) and found to solve all the CPMP in shorter time and in more promising result.

The Efficiency Evaluation of the Community Allocation to Healthcare Facilities in Malaysia

Malaysia is a developing country with an increase in population year by year. At the same time, the demand for public healthcare facilities also increases. Many complaints from people about inefficient services arise based on congestion and long waiting time when they are using public health facilities in Malaysia, however, it may result from the inefficiency in resource or demand allocation to a facility. In this chapter, a Capacitated Maximal Covering Location Problem (CMCLP) is used to study the current community allocation to the healthcare facilities in Mukim Batu, Selangor. This chapter also aims at evaluating the efficiency of allocating the community to the public healthcare based on a geographically defined region by applying ICER method. Importantly, we use ICER to evaluate the efficiency using the percentage assigned demand and the average travel distances as variable factors. Findings reveal that there is a need to plan for upgrading the existing facility rather than developing a new healthcare facility. The computational results also indicate that some of the health facilities are inefficient based on the percentage coverage demand while most of the health facilities are efficient based on the average travelled distances.

Comparing Methods for Lee–Carter Parameter’s Estimation for Predicting Hospital Admission Rates

The government hospital in Malaysia is prominent for the low cost of health care and medical treatment, and it had been reported that the hospital admission is increasing annually. This has led to the widespread problem of overcrowding. In order to assist the government to plan and manage demands for health services and health care needs, the prediction for future admission is outlined. The model is fitted to the matrix of admission rates, spanning the period of historical data from 2001 to 2011 for estimation. In particular, there are three types of estimation approaches used to generate the parameters of the Lee-Carter model which are singular value decomposition (SVD), iterative Newton–Raphson method (NR) and Poisson maximum likelihood estimation (PMLE). The resulting estimation generated by these three estimation approaches is then being compared and evaluated by two types of error measures which are mean squared error (MSE) and mean absolute percentage error (MAPE). The smallest values of MSE and MAPE indicate the better performance of the estimated parameters. The best estimation approach is subsequently used to forecast the admission rates of HRPZ II, Kota Bharu, for ten years ahead; using the out samples data from period 2012–2015. At the end of the study, it can be generally concluded that the occurrence of admission to HRPZ II, Kota Bharu, for both genders in each of the all broad age groups will slowly decrease along with the increment of years (2016–2025).

Predicting the “graduate on time (GOT)” of PhD students using binary logistics regression model

Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia’s largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

Identification of Seasonal Rainfall Peaks at Kelantan Using Fourier Series

This study aimed to identify the wet period, peaks of mean rainfall amount per rainy day at Kelantan River basin. Daily rainfall data from 12 selected rainfall stations for the period of 1975–2014 which comprises of three main areas such as inland, river, and coastal are analyzed. The estimated wet period, date, and value at peak of mean rainfall amount per rainy day will be identified using Fourier series and compared with the actual flood events in 2013/2014 and 2014/2015. The findings indicate that duration of wet periods obtained from the results of best fitting justifies the flood event occurred most recently. Moreover, the coastal area of Kelantan also shows the highest probability of rainfall amounts exceeding 60 mm.

Optimization of location routing inventory problem with transshipment

Location Routing Inventory Problem (LRIP) is a collaboration of the three components in the supply chain. It is confined by location-allocation, vehicle routing and inventory management. The aim of the study is to minimize the total system cost in the supply chain. Transshipment is introduced in order to allow the products to be shipped to a customer who experiences a shortage, either directly from the supplier or from another customer. In the study, LRIP is introduced with the transshipment (LRIPT) and customers act as the transshipment points. We select the transshipment point by using the p-center and we present the results in two divisions of cases. Based on the analysis, the results indicated that LRIPT performed well compared to LRIP.

Managing product stock keeping based on purchase association effect

Customer purchase behavior naturally affects the quantity or the choice of products they purchase. As such, purchase dependencies can be assumed to be closely related to the association the items or products they purchased together at one particular time. This study focuses on the association of product being purchased within one transaction based on the transaction made by the customers in retail shops and a supermarket. The objective is to adopt the inventory model with purchase dependencies in a real world and finally to compare the effect of purchase dependencies in the product availability level. Primary data were obtained from 130 customer sales transactions in the retail shop and the supermarket over a 7- day period. In order to demonstrate the effect of purchase dependencies on the total inventory cost, we adapted a new inventory model that utilizes purchase dependence. Finally, the test for significance of the difference is applied to show the effect of incorporating purchase dependencies in the inventory model. The simulation results demonstrated that the extended inventory models which have considered purchase dependencies showed reduction in lost sales and lost profit as well as total inventory cost. In conclusion, by incorporating purchase dependence element into inventory management process, we can minimize total inventory cost as well as lost profit.

Planning of public healthcare facility using a location allocation modelling: A case study

Finding the correct location of any facility and determining the demands which are to be assigned to it is very crucial in public health service. This is to ensure that the public gain maximum benefits. This article analyzes the previous location decisions of public primary healthcare (PHC) facilities in the district of Kuala Langat, Malaysia. With total population of 220214 (in 2010), the PHC in the district is currently served by 28 facilities. The percentages of total population covered (in 2007) within the maximum allowable distance of 3km and 5km are 69.7 percent and 77.8 percent respectively. This is very low compared to the Malaysian National Health Policy of Health for All or 100 percent coverage. The determination of health facility location should be planned carefully to further increase effective primary health service to the nation that is required for economic sustainability.