Project selection is a complex decision making process that is influenced by multiple and often conflicting objectives. The complexity of the project selection problem is due to the high number of projects from which a subset (portfolio) has to be chosen. We present a hybrid fuzzy rule-based multi-objective framework for sustainable project portfolio selection. The multiple and conflicting obje...

Nowadays, the main concerns of investors are choosing best portfolio in a way that highest possible return investment can be achieved by accepting least risk. In this regard, classical Markowitz model is one most widely used models which helps get closer to their goals. On other hand, data envelopment analysis (DEA) also practical technique analyze efficiency enterprises. However, real problems...

Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes...

Feature selection is one of the most pervasive problems in pattern recognition. It can be posed as a multiobjective optimisation problem, since, in the simplest case, it involves feature subset cardinality minimisation and performance maximisation. In many problem domains, such as in medical or engineering diagnosis, performance can more appropriately be assessed by ROC analysis, in terms of cl...

in the portfolio selection problem, the manager considers several objectives simultaneously such as the rate of return, the liquidity and the risk of portfolios. these objectives are conflicting and incommensurable. moreover, the objectives can be imprecise. generally, the portfolio manager seeks the best combination of the stocks that meets his investment objectives. the imprecise goal program...

In the context of Noisy Multi-Objective Optimization, dealing with uncertainties requires the decision maker to define some preferences about how to handle them, through some statistics (e.g., mean, median) to be used to evaluate the qualities of the solutions, and define the corresponding Pareto set. Approximating these statistics requires repeated samplings of the population, drastically incr...

Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision-making under uncertainty, namely the exploration versus exploitation dilemma, and therefore...

Avoiding the possibility of bankruptcy during the investment horizon is very important to multi-period portfolio management. This paper considers a multi-period fuzzy portfolio selection problem with bankruptcy control. A multi-period portfolio optimization model imposed by a bankruptcy control constraint in fuzzy environment is proposed on the basis of credibility theory. In the proposed model...