Optimization of Bank Portfolio Investment Decision Considering Resistive Economy

Increasing economy rsquo;s resistance against the menace of sanctions, various risks, shocks, and internal and external threats are one of the main national policies which can be implemented through bank investments. Investment project selection is a complex and multicriteria decisionmaking process that is influenced by multiple and often some conflicting objectives. This paper studies portfolio investment decisions in Iranian Banks. The main contribution of this paper is the creation of a project portfolio selection model that facilitates how Iranian banks would make investment decisions on proposed projects to satisfy bank profit maximization and risk minimization, while focus on national policies such as Resistance Economy Policies. The considered problem is formulated as a multiobjective integer programming model. A framework called MultiObjective Electromagnetismlike (MOEM) algorithm, is developed to solve this NPhard problem. To further enhance MOEM, a local search heuristic based on simulated annealing is incorporated in the algorithm. In order to demonstrate the efficiency and reliability of the proposed algorithm, a number of test are performed. The MOEM results are compared with two wellknown multiobjective genetic algorithms in the literature, i.e. Nondominated Sorting Genetic Algorithm (NSGAII) and Strength Pareto Evolutionary Algorithm (SPEAII) based on some comparison metrics. Also, these algorithms are compared with an integer linear programming formulation for small instances. Computational experiments indicate the superiority of the MOEM over existing algorithms.