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Comparison of Two Algorithms for Production Layout Improvement – The Application
Syed Ahmad Helmi bin Syed Hassan
Faculty of Mechanical Engineering, Universiti Teknologi Malaysia

Plant layout can be defined as a plan of optimum arrangement of industrial facilities, including personnel, operating equipment, storage space, material handling and all other supportive services. Every factory encounters layout problems from time to time and the operating efficiency of a manufacturing company is significantly influenced by its plant layout. This paper basically shows the needs of layout improvement at a glass manufacturing factory located in Penang, Malaysia. The objective of the project is to study the current layout and propose a better alternative, which can improve the material flow and the total traveled distances in the production plant. Systematic Layout Planning (SLP) has been used as the layout procedures in the study. Whereas Graph-based method and Pairwise Exchange method has been proposed as the algorithms for layout alternatives generation. These two algorithms are different from the type of algorithms and objective. Quantitative evaluation using from-to chart and qualitative evaluation using weighted factors comparison is then proposed to evaluate the alternatives generated. As a result, the best selection is done based on the evaluation.


Identifying Statistically Significant Protein Spots in 2-DE Protein Expression Data
Norhaiza Ahmad1 & J. Zhang2
1Department of Mathematics, Universiti Teknologi Malaysia,

81310 UTM Skudai, Johor, Malaysia

2Institute of Mathematics and Statistics, University of Kent, Canterbury, Kent, UK

Two-dimensional gel electrophoresis (2-DE) is one of the major techniques to simultaneously separate and quantitate thousands of cellular proteins. Due to the nature of 2-DE proteomic investigations there will always be’process variability’ factors in any data set collected in this way. Some of this variation will arise during sample preparation, gel running and staining, while further variation will arise from the gel analysis procedure. Therefore, in order to identify all significant changes in protein expression between biological samples when analysed by 2-DE, the system precision or ’error’, and how this correlates to protein abundance, must be known. Only then can the system be considered robust and investigators accurately and confidently report all observable statistically significant changes in protein expression. In this study we have undertaken 2-DE proteomic profiling on a series of cell lines with different recombinant antibody production rates. We introduce an expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have highlighted a small number of candidate proteins for further investigation.

Keywords: 2D-PAGE; proteomic profiling; NSO cells; variability; rank correlation


Regression Model for Forecasting Malaysian Electricity Load Demand
Zuhaimy Ismail & Faridatul Azan Jamaluddin
Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia.

81310 Skudai, Johor, Malaysia.
This paper presents a study on the use of time series regression model for forecasting Malaysian electricity demand with various non-deterministic factors influencing demand. The data of electricity demand in this study is provided by Tenaga Nasional Berhad, the main electricity supplier for Malaysia. Factors influencing the load demand include temperatures, holidays, daily and monthly seasonality. The data comprises of daily peak electricity load Lt (megawatts/hour, MWh-1) in Peninsular Malaysia from January 1997 until December 2000. Due to the nature of the data, time series regression model with autoregressive errors where the errors are serially correlated among observations is proposed. This enables the modeling of serially correlated error using Box-Jenkins autoregressive model. Forecast for one month ahead reveal that a time series regression model with load reduction weights yield better accuracy. Model validation is performed by comparing model predictions with the standard Box-Jenkins model. The results obtained bear out the suitability of the adopted methodology for the forecasting short-term electricity load demand.
Keywords: Regression; Forecasting; Electricity Load Demand; Box-Jenkins and Short-Term Forecasting.

Least Cost and Highest Demand Procedure as Feasible Solution for Dedicated Vehicle Routing Problem
Zuhaimy Ismail & Mohammad Fadzli Ramli
Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia.

81310 Skudai, Johor, Malaysia.

The most fundamental and well-studied routing problem is without doubt the Traveling Salesman Problem (TSP) while the Vehicle Routing Problem (VRP) is a generalization of the TSP. The VRP is to determine m vehicle routes, where a route is a tour that begins at the depots, visits a set of customers in a given order and returns to the depots. All customers must be visited exactly once and the total customer demand of a route must not exceed the vehicle capacity with the objective of minimizing the overall distribution costs. This paper presents various issues concerning VRP, focusing on a dedicated vehicle routine problem (DVRP), which is one variation in the problem. The VRP and its dedicated counterparts, the DVRP are introduced with the objective of finding the minimum routing traveled for one vehicle within a predetermined network using deterministic cost and quantity. In solving the VRP, its initial feasible solution does have a role in determining the final optimal solution. Here, two procedure algorithms namely the least cost and the demand priority are proposed as the initial feasible solution for the DVRP.


Selected Heuristic Algorithms for Solving Traveling Salesman Problem
Zuhaimy Ismail & Wan Rohaizad Wan Ibrahim
Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia.

81310 Skudai, Johor, Malaysia.

The traveling salesman problem (TSP) asks for the shortest route to visit a collection of cities and return to the starting point. Despite an intensive study by mathematicians, computer scientists, operation researcher, and others, over the past 50 years, it remains an open question whether or not an efficient general solution method exists. Given a collection of cities and the cost of travel between each pair of them, the traveling salesman problem, or TSP for short, is to find the cheapest way of visiting all of the cities and returning to your starting point. In the standard version we study, the travel costs are symmetric in the sense that traveling from the city X to city Y costs just as much as traveling from Y to X. The complexity of the problem increase in the size of the cities visited and testing every possibility for N city tour would be N! possible tours. A 30 city would have to measure the total distance of be 2.65X1032 different tours. Adding one more city would cause the time to increase by a factor of 31. Obviously, this is an impossible solution. This paper presents the product of an investigation research on the selected heuristic based on the most recent optimization techniques and at the same time produce a prototype program that can be used to generate a possible route for TSP. The heuristic methods used are based on the selected method such as the Greedy Search method, Simulated Annealing and Tabu Search. A user friendly optimization program developed using Microsoft C++ to solve the TSP and provides solutions to future TSP which may be classified into daily or advanced management and engineering problems.


An Electricity Load Demand Analysis Based on Day-Type using Exponential Smoothing
Zuhaimy Ismail & Rosnalini Mansor
Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia.

81310 Skudai, Johor, Malaysia.

The intrinsic uncertainties associated with demand forecasting become more acute when it is required to provide an invaluable dimension to the decision-making process in a period characterized by fast and dynamic changes. This dynamic nature of the demand for electricity call for more research in areas such as the estimation methodology of peak demand, factors affecting load demand, the system used, the organizational structure involved in forecasting and the types of forecasting methods. One of the main factors that influence electric demand is types of day such as weekday, weekend and holiday. The behavior patterns of the end-user are based on a few actual observations, which are divided into daily and annual weekly load profile. The annual daily and weekly load profile is used to explain the general lifestyle throughout the year. The daily load profiles for a typical week and during festive season, is used to explain behavioral pattern during a typical week and an hourly load profile is used to explain the lifestyle on a normal working day. This paper presents the influence of types of day in forecasting electricity load demand in Malaysia. We use separate forecasting model to forecast day and named the weekday and weekend model. In this study we include the analysis of load demand using exponential smoothing model of electricity load forecasting. We use several exponential techniques to forecast short-term electricity demand and compare performance among them. The data used was the 1826 daily maximum demand time series from 1 January 2001 to 31 December 2005. A case study was conducted at Tenaga Nasional Berhad (TNB), a public listed electric company who builds, operates and maintains electricity transmission and distribution network in Peninsular Malaysia. TNB has the largest generation capacity of over 10450 MW that accounts for about 60% of the total power installed (17300MW). The other 40% is provided by the Independent Power Producers (IPPs). The result shows that Log seasonal Exponential Smoothing is a reasonable good model for forecasting daily load demand.


Mixed Convection Boundary Layer of a Viscoelastic Fluid near a Stagnation Point
Nur Ilyana Anwar Apandi, Norsarahaida Amin & Sharidan Shafie
Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia.

A mathematical model for the two dimensional boundary layer flow of a viscoelastic fluid near the stagnation point of a circular cylinder is discussed. Viscoelastic fluid is an incompressible non-Newtonian second-grade fluid that exhibits a combination of both fluid and solid characteristics. Problems involving viscoelastic fluids are encountered in several industrial processes particularly in the polymer industry. The governing equations which consist of third order non-linear partial differential equations are transformed to a fourth order ordinary differential equation, which is then solved numerically using the Keller-box method, by augmenting an extra boundary condition at infinity. Numerical results obtained in the form of velocity distributions and temperature profiles are presented for a range of values of the dimensionless viscoelastic fluids parameter, K. Increasing the viscoleastic parameter has the effect of raising both the velocity and heat transfer performance.


The Parallel AGE Method for Solving Incomplete Blow-Up Problem Using Heterogeneous Multiprocessor Systems
Norma Alias, Nurul Ain Zhafarina Muhamad
Department of Mathematics, Faculty of Science,

University Technology Malaysia, 81310 Skudai, Johor, Malaysia

High performance computing (HPC) is build from supercomputers and computer clusters. Computing systems comprised of multiple (usually mass-produced) processors linked together in a single system with commercially available interconnects. The HPC archtecturer under consideration is called heterogeneous multiprocessor systems. This paper concentrates on solving incomplete blow-up using the Alternating Group Explicit Scheme (AGE) algorithms by using the heterogeneous multiprocessor systems. The standard numerical procedure is based on Gauss Seidel method. Incomplete blow-up is a condition under the quasilinear heat equation. The Porous Medium Equation (PME) with power source admitting incomplete blow-up. It also used as one of the process in the industry such as in filtration. This filtration process has been used globally in the medical and laboratory applications. The performance measurements such as convergent rate, number of iteration, execution time, speedup, efficiency, effectiveness, computational complexity and stability are also investigated.


High performance computing, heterogeneous multiprocessor systems, Alternating Group Explicit Scheme, incomplete blow-up

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