The algorithm for optimization of a credit portfolio has not been fully demonstrated. This paper fills the gap in the literature by presenting a general approach for optimizing a credit portfolio by minimizing the default risk of the entire portfolio. Default risk is measured with quadratic...

In recent years genetic algorithms have emerged as a useful tool for the heuristic solution of complex discrete optimisation problems. In particular there has been considerable interest in their use in tackling problems arising in the areas of scheduling and timetabling. However, the classical...

The movement of the human body is simulated with a virtual, mechanical, robot-type model (articulated figure) consisting of 14 solid subbodies. The shapes of these 14 subbodies are initially a ball, cylinders or rectangular boxes. The model is initially adapted, in particular the dimensions of...

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...

Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and...

A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of...