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Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most ...

Over the past few years, a continually increasing number of research efforts have investigated the application of evolutionary computation techniques for the solution of scheduling problems. Scheduling problems can pose...

Allocation of the components (tasks) of a parallel program to processors in a multiprocessor or a multicomputer system take full advantage of the computational power provided by the system. Evolutionary approaches has b...

Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its econ...

The flow shop scheduling problem (FSSP) has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main obj...

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is know...

Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or...