Parallel machine scheduling, involves the allocation of jobs to the system resources (a bank of machines in parallel). A basic model consisting of m machines and n jobs is the foundation of more complex models. Here, jobs are allocated according…

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality…

Determining an optimal schedule to minimize the completion time of the last job abandoning the system (makespan) becomes a very difficult problem when there are more than two machines in the flow shop. Due both to its economical impact and…

In the restricted single-machine common due date problem the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties, while for the weighted tardiness problem the goal is to find…

The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules.…

When using tableaux algorithms to reason about Description Logics (DLs), new information is inferred from the models considered while trying to achieve knowledge satisfiability. By focusing the ontology change problem, we consider an environment where DLs are the logical formalization…

In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the…

In an m-machines n-jobs flow-shop sequencing problem each job consists of m operations and each operation requires a different machine, so n jobs have to be processed in the same sequence on m machines. The processing time of each job…