Genetic Algorithm for Optimal Vendor Payment Schedule of Transportation Company

Abstract

Nowadays, businesses in any sector are under pressure to do more with less. Company cannot afford to pay more and squander opportunities to free up their company's cash, i.e. working capital. Good working capital gives greater availability to the cash trapped on your balance sheet which is beneficial to fund growth, reduce costs, enhance service levels and seize new investment opportunities. There are numerous ways to free up working capital, and one of the strategies is through account payable. Account payable are amounts due to vendor or supplier for goods or services received that have not yet been paid for. Thus, this paper focuses on the proper vendor payment schedule as one of the approaches to sustain the liquidity of business. Optimizing the vendor payment schedule could be observed through their Net Present Value (NPV). NPV is the difference between the present value of cash inflows and outflows. Therefore, our aim is to optimize the vendor payment schedule by maximizing their NPV. Genetic Algorithm (GA) is implemented in determining the optimal vendor payment schedule. Two GA parameters, which are generation number and population size, have been analyzed and optimized in order to meet the maximum NPV. The results show that the GA is efficient in maximizing the NPV of vendor payment schedule.