Linear programming (LP) is an important field of optimization. Even though, interior point methods are polynomial algorithms, many LP practical problems are solved more efficiently by the primal and dual revised simplex methods (RSM); however, RSM has a poor performance in hard LP problems (HLPP) as in the Klee-Minty Cubes problem. Among LP methods, the hybrid method known as Simplex-Genetic (S...

R surface methodology (RSM) is a widely used method for simulation optimization. Its strategy is to explore small subregions of the decision space in succession instead of attempting to explore the entire decision space in a single attempt. This method is especially suitable for complex stochastic systems where little knowledge is available. Although RSM is popular in practice, its current appl...

It is well known that the generalization capability is one of the most important criterions to develop and evaluate a classifier for a given pattern classification problem. The localized generalization error model (RSM) [2, 12] recently proposed by Ng et al. provides a more intuitive look at the generalization error. Although RSM gives a brand-new method to promote the generalization performanc...

In this study of coagulation operation, a comparison was made between the optimum jar test values for pH, coagulant and coagulant aid obtained from traditional methods (an adjusted one-factor-at-a-time (OFAT) method) and with central composite design (the standard design of response surface methodology (RSM)). Alum (coagulant) and polymer (coagulant aid) were used to treat a water source with v...

In this letter, we introduce the Riemann sum method (RSM) as an effective tool for the design of sum-of-cisoids (SOC) simulators for narrowband mobile Rayleigh fading channels under non-isotropic scattering conditions. We compare the performance of the RSM with that of the generalized method of equal areas (GMEA) and the Lp-norm method (LPNM), which were until now the only methods available for...

This cohort study evaluated whether rescue spontaneous maturation (RSM) could be a valid method to increase the number of embryos available for transfer and whether transfers with RSM-derived embryos would contribute to clinical outcomes of poor-responder patients in ovarian stimulation cycles. The study included 440 patients undergoing intracytoplasmic sperm injection cycles in which fewer tha...

A highly sensitive and selective high performance liquid chromatographic fluorescence detection method has been developed and validated for the quantification of rivastigmine in rat plasma and brain. Protein precipitation and one-step liquid-liquid extraction techniques were utilized for the extraction of RSM from brain and plasma, respectively, along with an internal standard. The chromatograp...

A resource space model (RSM) is a model for specifying, sharing and managing versatile Web resources with a universal resource view. A normal resource space is a semantic coordinate system with independent coordinates and mutual-orthogonal axes. This paper first introduces the main viewpoint and basic content of the RSM, and then proposes a four-step method for designing the logical-level resou...

In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were investigated. The experiments were carried out based on a 3-level, 4-variable Box-Behnken design. The amount of zinc was considered as a function of four independent variables, namel...

Abstract: Robust design (RD), implemented in statistical and mathematical procedures to simultaneously minimise the process bias and variability, is widely used in many areas of engineering and technology to represent complex real-world industrial settings. For RD modelling and optimisation, response surface methodology (RSM) is often utilised as an estimation method to represent the functional...