Research in metaheuristics for combinatorial optimization problems has lately experienced
a noteworthy shift towards the hybridization of metaheuristics with other techniques for …

Random-key genetic algorithms were introduced by Bean (ORSA J. Comput. 6: 154–160,
1994) for solving sequencing problems in combinatorial optimization. Since then, they have …

GRASP is a multi-start metaheuristic for combinatorial optimization problems, in which each
iteration consists basically of two phases: construction and local search. The construction …

Job shop scheduling has been the focus of a substantial amount of research over the last
decade and most of these approaches are formulated and designed to address the static job …

This paper presents a hybrid genetic algorithm for the job shop scheduling problem. The
chromosome representation of the problem is based on random keys. The schedules are …

Workflow scheduling is one of the key issues in the management of workflow execution.
Scheduling is a process that maps and manages execution of inter-dependent tasks on …

Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …

Grid applications require allocating a large number of heterogeneous tasks to distributed
resources. A good allocation is critical for efficient execution. However, many existing grid …

After a decade of research into the area of artificial immune systems, it is worthwhile to take
a step back and reflect on the contributions that the paradigm has brought to the application …

The job shop scheduling problem is one of the most important and complicated problems in
machine scheduling and is considered to be a member of a large class of intractable …