By R. Venkata Rao
Advanced Modeling and Optimization of producing Processes offers a finished evaluation of the most recent overseas examine and improvement tendencies within the modeling and optimization of producing approaches, with a spotlight on machining. It makes use of examples of assorted production approaches to illustrate complex modeling and optimization strategies. either simple and complicated options are offered for numerous production procedures, mathematical types, conventional and non-traditional optimization options, and genuine case experiences. the result of the applying of the proposed equipment also are lined and the ebook highlights the main invaluable modeling and optimization thoughts for attaining top strategy functionality. as well as protecting the complex modeling, optimization and environmental points of machining methods, Advanced Modeling and Optimization of producing Processes additionally covers the most recent technological advances, together with fast prototyping and tooling, micromachining, and nano-finishing. Advanced Modeling and Optimization of producing Processes is written for designers and production engineers who're chargeable for the technical features of product consciousness, because it offers new versions and optimization strategies to make their paintings more straightforward, extra effective, and more suitable. it's also an invaluable textual content for practitioners, researchers, and complex scholars in mechanical, business, and production engineering.
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Extra info for Advanced Modeling and Optimization of Manufacturing Processes: International Research and Development
If the problem is not in posynomial form, variable substitution may be used to convert the original problem into a primal form. Thereafter, the primal problem is converted into an equivalent dual problem expressed in terms of set of dual variables. This transformation is achieved using arithmetic–geometric-mean equality principle. Once the optimal dual variables are found by solving the dual non-linear programming problem, the primal solution can be obtained by solving the set of simultaneous equations formed.
Tabus are stored in the short term memory of search called tabu list. When a best vector is determined from the sample of decision vectors in the neighborhood of the current decision vector, a move is made from current decision vector to the best decision vector not in the tabu list. The tabu list contains a certain number of last decision vectors visited. The best decision vector replaces the oldest vector in the tabu list and the survival vectors in the list are given tabu active status. Tabu active vectors are forbidden to create the sample of decision vectors in the neighborhood.
The branch and bound method is very effective in solving the mixed-integer linear and non-linear programming problems. The method was originally developed by Land and Doig  to solve integer linear programming problems and was later modified by Dakin . In branch and bound method, the integer problem is not directly solved. Rather, the method first solves the continuous problem obtained by relaxing the integer restrictions on the variables. If the solution to the continuous problem happens to be an integer solution, it represents the optimum solution of integer problem.