Nur Jumaadzan Zaleha Mamat

Fund allocation using capacitated vehicle routing problem

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor’s objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor’s profit.

Vehicle routing problem in investment fund allocation

Since its introduction by Dantzig and Ramser in 1959, vehicle routing problem keeps evolving in theories, applications and variability. The evolution in computing and technology are also important contributors to research in solving vehicle routing problem. The main sectors of interests among researchers and practitioners for vehicle routing problem are transportation, distribution and logistics. However, literature found that concept and benefits of vehicle routing problem are not taken advantages of by researchers in the field of investment. Other methods found used in investment include multi-objective programming, linear programming, goal programming and integer programming. Yet the application of vehicle routing problem is not fully explored. A proposal on a framework of the fund allocation optimization using vehicle routing problem is presented here. Preliminary results using FTSE Bursa Malaysia data testing the framework are also given.

Optimizing investment fund allocation using vehicle routing problem framework

The objective of investment is to maximize total returns or minimize total risks. To determine the optimum order of investment, vehicle routing problem method is used. The method which is widely used in the field of resource distribution shares almost similar characteristics with the problem of investment fund allocation. In this paper we describe and elucidate the concept of using vehicle routing problem framework in optimizing the allocation of investment fund. To better illustrate these similarities, sectorial data from FTSE Bursa Malaysia is used. Results show that different values of utility for risk-averse investors generate the same investment routes.

Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem

Capacitated Vehicle Routing Problem-Investment Fund Allocation Problem (CVRP-IFAP) provides investors with a sequence of assets to allocate their funds into. To minimize total risks of investment in CVRP-IFAP covariance values measure the risks between two assets. Another measure of risks are correlation values between returns. The correlation values can be used to diversify the risk of investment loss in order to optimize expected return against a certain level of risk. This study compares the total risk obtained from CVRP-IFAP when using covariance values and correlation values. Results show that CVRP-IFAP with covariance values provides lesser total risks and a significantly better measure of risk.

Water quality study at Skudai River, 2002 – 2006

Assessing the level of river water quality periodically is important in ensuring that the river water is safe for consumption. This study investigates the level of water quality at Skudai River from year 2002 to 2006. Twenty parameters were identified and used in this analysis. These twenty parameters are recorded at nine monitoring stations located along the Skudai River. Multivariate statistical techniques i.e. factor and cluster analysis were used in this analysis. From this analysis we managed to group the monitoring stations into three categories: seriously polluted, moderately polluted and clean.

Vehicle routing problem and capacitated vehicle routing problem frameworks in fund allocation problem

Two new methods adopted from methods commonly used in the field of transportation and logistics are proposed to solve a specific issue of investment allocation problem. Vehicle routing problem and capacitated vehicle routing methods are applied to optimize the fund allocation of a portfolio of investment assets. This is done by determining the sequence of the assets. As a result, total investment risk is minimized by this sequence.