A novel robust optimization algorithm is demonstrated, which attempts to account for expected coating errors. Monte Carlo simulations show the robust approach improves manufacturing yields relative to conventional optimization. c © 2010 Optical Society of America OCIS codes: (310.6805) Theory and design; (310.4165) Multilayer design

in this paper, integrated direct and reverse logistics considering production, distribution, customer, devastation, retrieval centers under uncertainty are developed. in this model, cost parameters are not certain, thus the scenario-based robust optimization method is applied. the aim of this model is to minimize the total cost and obtain a robust solution. finally, a practical case study is pr...

The thermal management of modern aircraft has become more challenging as aircraft capabilities have increased. The use of thermally resistant composite skins and the desired for low observability, reduced ram inlet size and number, has reduced the ability to transfer heat generated by the aircraft to the environment. As the ability to remove heat from modern aircraft has decreased, the heat loa...

In this paper, a new robust metaheuristic optimization algorithm called improved time evolutionary optimization (ITEO) is applied to design reinforced concrete one-way ribbed slabs. Geometric and strength characteristics of concrete slabs are considered as design variables. The optimal design is such that in addition to achieving the minimum cost, all design constraints are satisfied under Amer...

A dual structural fused system consists of replaceable ductile elements (fuses) that sustain major seismic damage and leave the primary structure (PS) virtually undamaged. The seismic performance of a fused structural system is determined by the combined behavior of the individual PS and fuse components. In order to design a feasible and economic structural fuse concept, we need a procedure to ...

We study the empirical likelihood approach to construct confidence intervals for the optimal value and the optimality gap of a given solution, henceforth quantify the statistical uncertainty of sample average approximation, for optimization problems with expected value objectives and constraints where the underlying probability distributions are observed via limited data. This approach relies o...

Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electrom...

this paper proposes a family of robust counterpart for uncertain linear programs (lp) which is obtained for a general definition of the uncertainty region. the relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. those properties lead us to characterize primal and dual robust counterparts. the researchers show t...

This study presents a parameter coordination and robust optimization approach based on knowledge network modeling. The method allows multidisciplinary designer to synthetically coordinate and optimize parameter considering multidisciplinary knowledge. First, a knowledge network model is established, including design knowledge from assembly, manufacture, performance, and simulation. Second, the ...