Nurse rostering is a well-known highly constrained scheduling problem requiring assignment of shifts to nurses satisfying a variety of constraints. Exact algorithms may fail to produce high quality solutions, hence (meta)heuristics are commonly preferred as solution methods which are often designed and tuned for specific (group of) problem instances. Hyper-heuristics have emerged as general sea...

In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuris...

The paradigm of distributed computation in heterogeneous resources, grid computing, has given rise to a large amount of research on resource scheduling. This paper presents a Meta-Scheduler for grid computing that does not need any given information about tasks length or tasks arrival time unlike traditional dynamic heuristics. Our Meta-Scheduler is of multi-criteria type, because it solves two...

Timetable generation is a combinatorial optimization problem. Meta Heuristic methods and Evolutionary Algorithms have given the best results when it comes to solving the problem of timetable generation. In our paper the problem of timetable generation for the Computer Science and Engineering Dept. of BMS College of Engineering is solved with the help of Genetic Algorithm and Tabu Search which b...

Meta-heuristics are an effective paradigm for solving large-scale combinatorial optimization problems. However, the development of such algorithms is often very time-consuming as they have to be designed for a concrete problem class with little or no opportunity for reuse. In this paper, we present a generic software framework that is able to handle different types of combinatorial optimization...

Abstract Optimization problems are frequent in several fields, such as the different branches of Engineering. In some cases, objective function exposes mathematically exploitable properties to find exact solutions. However, when it is not case, heuristics appreciated. This situation occurs involves numerical simulations and sophisticated models reality. Then, population-based meta-heuristics, g...