Capabilities of enhanced simulated-annealing-based algorithms in solving process planning problems in reconfigurable manufacturing are investigated. The algorithms are enhanced by combining variants of the simulated annealing technique with other algorithm concepts such as (i) knowledge exploitation and (ii) parallelism. Four configurations of simulated annealing algorithms are devised and enga...

in today’s dynamic market, organizations must be adaptive to market fluctuations. in addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. therefore, this paper considers the problem of arranging and rearranging, when there are changes in product mix and demand, manufacturing facilities such that the sum of material handling and rearr...

We analyze simulated annealing applied to multiple-valued programmable logic array (MVL PLA) design. Of spec@c interest is the use of parallel processors. We consider the use of loosely-coupled, coarsegrainedparallel systems, and study the relationship between the quality of the solution and computation time, on the one hand, and simulated annealing parameters, start temperature, cooling rate, ...

mutual information (mi) is a widely used similarity metric for multimodality image registration. however, it involves an extremely high computational time especially when it is applied to volume images. moreover, its robustness is affected by existence of local maxima. the multi-resolution pyramid approaches have been proposed to speed up the registration process and increase the accuracy of th...

In this paper we describe the use of coupling to interconnect different Simulated Annealing (SA) processes. The objective is to allow cooperative behavior among the processes in order to improve performance. Coupled Simulated Annealing (CSA) permits a high degree of parallelization while delivering much better results than a typical Parallel SA (PSA) algorithm. This is possible due to the intro...

Real Options for Project Schedules (ROPS) has three recursive sampling/optimization shells. An outer Adaptive Simulated Annealing (ASA) optimization shell optimizes parameters of strategic Plans containing multiple Projects containing ordered Tasks. A middle shell samples probability distributions of durations of Tasks. An inner shell samples probability distributions of costs of Tasks. PATHTRE...