A tomographic reconstruction method based on Monte Carlo random searching guided by the information contained in the projections of radiographed objects is presented. In order to solve the optimization problem, a multiscale algorithm is proposed to reduce computation. The reconstruction is performed in a coarse-tofine multigrid scale that initializes each resolution level with the reconstructio...

Preliminary ship design is currently more art than science, heavily dependent on highly experienced naval architects. The use of genetic algorithms is proposed as a method for improving ship design through more effective exploration of the design space. Three main points are advanced in this paper. First, genetic algorithms (GA) are a highly effective tool for the exploration of large-scale, no...

Evolutionary computation techniques, which are based on a powerful principle of evolution: survival of the ttest, constitute an interesting category of heuristic search. In other words, evolutionary techniques are stochastic algorithms whose search methods model some natural phenomena: genetic inheritance and Darwinian strife for survival. Any evolutionary algorithm applied to a particular prob...

Sets of DNA strands that satisfy combinatorial and thermodynamic properties play an important role in various approaches to biomolecular computations, nano structure design, molecular tagging, and DNA microarrays. The problem of designing such sets of DNA strands appears to be computationally hard. This thesis introduces new algorithms for design of DNA strand sets that satisfy any of several c...

Scheduling is one of the main problems that need to be solved by high-level hardware and software compilers. Existing heuristics are often incapable of finding feasible solutions for practical examples, because the tight time and resource constraints make the feasible-solution subspace very small compared to the size of the full search space. For that reason, constraint-analysis techniques that...

VoD, S., Steiner’s problem in graphs: heuristic methods, Discrete Applied Mathematics 40 (1992) 45-72. Real world problems arising in the layout of connection structures in networks as e.g. in VLSI design may often be decomposed into a number of well-known combinatorial optimization problems. Steiner’s problem in graphs is included within this context. According to its complexity one is interes...

Facility location problems form an important class of industrial optimization problems. These problems typically involve the optimal location of facilities. For our purposes, a facility is just a physical entity that assists with the provision of a service or the production of a product. Examples include: schools, ambulance depots, emergency care centers, firestations, workstations, libraries e...

Current methods f o r mechanical program v e r i f i c a t i o n r e q u i r e a complete p red i ca te s p e c i f i c a t i o n on each l o o p . Because t h i s i s ted ious and e r r o r p r o n e , producing a program w i t h complete, c o r r e c t p red i ca tes i s reasonably d i f f i c u l t and would be f a c i l i t a t e d by machine ass i s t ance . This paper d iscusses h e u r i...

abstract Heuristic evaluation has proven popular for desktop and Web interfaces, both in practical design and as a research topic. Compared to full user studies, heuristic evaluation can be highly cost-effective, allowing a large proportion of usability flaws to be detected ahead of full development with limited resource investment. Mobile computing shares many usability issues with more conven...

The transformation or derivation problem treated by most "problem-solving" programs is expressed in a formal notation, and various methods for "problem-solving" are reviewed. The conventio­ nal search tree is generalized into a search lattice which can accomodate multiple-input opera­ tors, e.g. resolution. The paper argues that descriptions of heuristic methods can be signi­ ficantly compacted...