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Parallel approaches to parametric optimization and the convergence of interactive decision support

Wierzbicki A.

Control and Cybernetics

2000

Vol. 29, no 1

427-444

In the perspective of parallel processing, a new sense of parametric optimization might be promoted. The paper shows that it, is possible to propose new parallel versions of basic optimization algorithms, as well as an advanced method of securing convergence in interactive mnltiobjective optimization and decision support, all based on a modified concept of parametric embedding. This general idea is exemplified for the case of the simplex algorithm of linear programming by a parameterized and coarse-grain parallel augmented simplex algorithm, where a linear optimization problem can be embedded into a multiple-ohjective family which introduces diversified directions of search cutting through the interior of the original admissible set. For the case of nonlinear programming, a parameterized and coarse-grain parallel variable metric pulsar algorithm is shortly presented, where parallel directional searches are combined with a parametrized variable metric to produce a pulsating, robust nonliear programming algorithm. These two examples concern very basic optimization tools ; at the other end of the spectrmn of optimization-related methods, a general method called outranking trials of securing convergence of interactive multiobjective optimization and decision suport is obtained through parameterizing an outranking relation and using basic properties of order-consistent achievement functions in reference point methodology for testing the existence of outranking points by parallel optimization runs. Thus, the paper presents the use of parallel processing to solve a wide range of modified parametric embedding problems related to optimization and decision support.

Assignment and sequencing of parts to autonomous workstations

Lucertini M., Nicolo F., Smriglio S.

Control and Cybernetics

2000

Vol. 29, no 1

221-236

We present an optimization-based coordination protocol among autonomous workstations in a multiprocessor stage devoted to painting of the shutters in a furniture production process. The coordination aims to maximize the number of parallel operations executable at each machine cycle, while fulfilling constraints on the unique-copy tools. The mechanism is derived by a distributed implementation of a bipartite matching algorithm. The resulting procedure is shown to be compatible with the several autonomous decisions characterizing the process.