We present a new interactive procedure for evolutionary multiobjective optimization involving the decision rule preference model in the search for the best compromise solution. As usual in the interactive multiobjective optimization, preference elicitation phases alternate with optimization...

We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity...

Designing optimal products is one of the most critical activities for a firm to stay competitive. Except for genetic algorithms, previous approaches that solve the optimal product line design problem provide the decision maker with a single best solution. Furthermore, they assume a static...

We present a mathematical analysis of the long-run behavior of genetic algorithms that are used for modeling social phenomena. The analysis relies on commonly used mathematical techniques in evolutionary game theory. Assuming a positive but infinitely small mutation rate, we derive results that...

The growing demand for electronic devices has made the manufacturing of printed circuit boards (PCBs) a promising industry over the last decades. As the demand for printed circuit boards increases, the industry becomes more dependent on highly automated assembly processes using Surface Mounting...

Portfolio selection problem is a major subject in finance where investors deal with selecting satisfying portfolio which is composed of a vast number of risky assets, under some restricting criteria that are defined by themselves. Asset prices can be effected from different events, such as...

Portfolio optimisation for a Fund of Hedge Funds (“FoHF”) has to address the asymmetric, non-Gaussian nature of the underlying returns distributions. Furthermore, the objective functions and constraints are not necessarily convex or even smooth. Therefore traditional portfolio optimisation...

This paper discusses the role that Genetic Algorithms (GA) can have in determining asset allocation for multi sector funds. We present an asset allocation model where the investors' utility function departs from the quadratic utility function assumed by the standard Mean-Variance optimisation....

Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear- quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...

Combinatorial optimization problems are usually NP-hard and the solution space of them is very large. Therefore the set of feasible solutions cannot be evaluated one by one. Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are metaheuristic techniques...