A New Interactive Algorithm for Continuous Multiple Criteria Problems: A Portfolio Optimization Example

© 2021 World Scientific Publishing Company.In continuous multiple criteria problems, finding a distinct preferred solution for a decision maker (DM) is not straightforward. There are few recent studies proposed for this task, and the algorithms developed are cognitively difficult and complex for the DM in general. We propose a novel interactive algorithm to guide the DM in converging highly-preferred solutions in continuous multiple criteria problems. We test our algorithm on portfolio optimization problems formed with the stocks included in the S&P 100 index using expected return, liquidity, conditional value at risk, and mean absolute deviation as criteria. We simulate DM responses with linear and nonlinear preference functions and use various weights for the criteria. The experiments show that our algorithm is able to find highly-preferred solutions in considerably low number of iterations. We also test our algorithm against benchmark algorithms and demonstrate that our algorithm produces superior or comparable results

A stochastic programming approach to multicriteria portfolio optimization

We study a stochastic programming approach to multicriteria multi-period portfolio optimization problem. We use a Single Index Model to estimate the returns of stocks from a market-representative index and a random walk model to generate scenarios on the possible values of the index return. We consider expected return, Conditional Value at Risk and liquidity as our criteria. With stocks from Istanbul Stock Exchange, we make computational studies for the two and three-criteria cases. We demonstrate the tradeoffs between criteria and show that treating these criteria simultaneously yields meaningful efficient solutions. We provide insights based on our experiments

EFFECTS OF MULTIPLE CRITERIA ON PORTFOLIO OPTIMIZATION

We study the effects of considering different criteria simultaneously on portfolio optimization. Using a single-period optimization setting, we use various combinations of expected return, variance, liquidity and Conditional Value at Risk criteria. With stocks from Borsa Istanbul, we make computational studies to show the effects of these criteria on objective and decision spaces. We also consider cardinality and weight constraints and study their effects on the results. In general, we observe that considering alternative criteria results in enlarged regions in the effi-cient frontier that may be of interest to the decision maker. We discuss the results of our experiments and provide insights

A Multicriteria Method to Form Optional Preventive Maintenance Plans: A Case Study of a Large Fleet of Vehicles

IEEEMotor vehicles are composed of a large number of parts, and planning the maintenance activities of different parts is a crucial decision that affects system reliability, operation costs, and capacity requirements of service providers. We propose a systematic method to determine the critical parts that should be handled with extra preventive maintenance (PM) and prepare alternative PM plans with different levels of cost and capacity usage. Our method uses a multicriteria decision-making approach to determine the critical parts and conducts statistical reliability analysis with failure data and expert knowledge to create the maintenance plans. We use the proposed method in a case study to determine optional PM packages that would support regular PM practices in the after-sales service of a large motor vehicle manufacturer. The main aim of the case study is to increase the satisfaction of customers who are more sensitive to failures, such as carriers of food and medical supplies. The results show that the optional PM packages can decrease the cost of failures while obeying the capacity limitation of the company