Common issues in discrete optimization and discrete-eventsimulation

This note studies and exploits common issues between discrete-event simulation models and algorithms for discrete optimization problems to prove that two discrete-event simulation search problems are NP-hard. More specifically, NEIGHBORHOOD seeks a sequence of events such that two distinct states can be accessed, one state after executing all but the last k events and another state after executing all the events, while INITIALIZE seeks a sequence of events such that executing the sequence with one particular initial event results in a particular state being reached, while for a second initial event, that particular state cannot be reached. Implications of these results for discrete-event simulation modeling and analysis (e.g., assessing when steady state, termination conditions have been reached, or optimal input parameters values for simulation optimization have been established) as well as for discrete optimization problems (e.g., assessing a priori the effectiveness of a neighborhood for simulated annealing or tabu search) are discussed     

Abiotic stress of ZnO‐PEG,ZnO‐PVP,CuO‐PEG and CuO‐PVP nanoparticles enhance growth,sweetener compounds and antioxidant activities in shoots of Stevia rebaudiana Bertoni

Nanoparticles are known to play remarkable role as abiotic stress elicitors in plants. This study reports the comparative analysis of effects produced by capped [zinc oxide (ZnO)‐polyethylene glycol (PEG), ZnO‐polyvinyl pyrrolidone (PVP), copper oxide (CuO)‐PEG, CuO‐PVP] and uncapped (ZnO and CuO) nanoparticles on the medicinal plant, Stevia rebaudiana raised in vitro for the production of commercially important sweetener compounds. In context of shoot organogenesis, ZnO‐PEG, ZnO‐PVP, CuO‐PEG, CuO‐PVP were employed to the growth medium that resulted in increased growth parameters, and larger content of steviol glycosides as compared to the shoots raised in medium containing ZnO and CuO, revealed by high‐performance liquid chromatography. In the meanwhile, non‐enzymatic antioxidant activities including total phenolic content, total flavonoid content, total antioxidant capacity, total reducing power and 2,2‐diphenyl‐1‐picryl hydrazyl‐free radical scavenging activity were calculated and showed comparatively greater amounts in shoots grown in medium containing capped ZnO or CuO nanoparticles. Furthermore, the ZnO and its derivatives revealed to be more reactive at 1 mg/l of concentration. Whereas, the CuO and its derivatives produced greater response on Stevia at 10 mg/l concentration of nanoparticles. This study paves the way for more such studies encompassing capped and uncapped nanoparticles and their ultimate effect on in‐vitro grown plant tissues for the production of active metabolites on industrial scale.Inspec keywords: nanoparticles, chromatography, resins, polymers, zinc compounds, copper compounds, food technology, agricultureOther keywords: nanoparticles, sweetener compounds, antioxidant activities, Stevia rebaudiana Bertoni, abiotic stress elicitors, zinc oxide‐polyethylene glycol, zinc oxide‐polyvinyl pyrrolidone, copper oxide‐polyethylene glycol, medicinal plant, shoot organogenesis, steviol glycosides, high‐performance liquid chromatography, nonenzymatic antioxidant activities, total phenolic content, total flavonoid content, total antioxidant capacity, total reducing power, 2,2‐diphenyl‐1‐picryl hydrazylfree radical scavenging activity, derivatives, active metabolite production, copper oxide‐polyvinyl pyrrolidone     

Computing efforts allocation for ordinal optimization and discreteevent simulation

Ordinal optimization has emerged as an efficient technique for simulation and optimization. Exponential convergence rates can be achieved in many cases. In this paper, we present a new approach that can further enhance the efficiency of ordinal optimization. Our approach intelligently determines the optimal number of simulation replications (or samples) and significantly reduces the total simulation cost. Numerical illustrations are included. The results indicate that our approach can obtain an additional 74% computation time reduction above and beyond the reduction obtained through the use of ordinal optimization for a 10-design example     

Determination of process parameters through a mechanistic force model of milling operations

Mechanistic process parameters for the end milling operation are determined for 11L17 free machining steel, 2024 aluminum and 62-35-3 free machining brass by analyzing the measured cutting force data and using a mechanistic force model. It has been found that pressure and friction acting on the cutter-chip interface decrease with the increase of feed rate, while the cutting speed has a negligible effect on some of the material-dependent parameters. Process parameters are summarized into empirical equations as functions of feed rate and tool rotation angle for each workpiece material. The use of sampled force data in the computation of the process parameters reduces the amount of testing greatly compared to those methods that utilize only average force data.