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This paper presents a tabu search approach for the job-shop scheduling problem. Although the problem is NP-hard, satisfactory solutions have been obtained recently by tabu search. However, tabu search has a problem-speci®c and parametric structure. Therefore, in the paper, we focussed on the tabu search strategies and parameters such as initial solution,(More)
This paper presents an optimization via simulation approach to solve dynamic flexible job shop scheduling problems. In most real-life problems, certain operation of a part can be processed on more than one machine, which makes the considered system (i.e., job shops) flexible. On one hand, flexibility provides alternative part routings which most of the time(More)
An artificial neural network (ANN) model was used to predict removal efficiency of Lanaset Red (LR) G on walnut husk (WH). This adsorbent was characterized by FTIR-ATR. Effects of particle size, adsorbent dose, initial pH value, dye concentration, and contact time were investigated to optimize sorption process. Operating variables were used as the inputs to(More)
The purpose of this study is to examine clinical progress and hemodynamic and electrocardiologic features (QT depression and heart rate variability [HRV]) of patients exposed to a scorpion bite. Seventeen patients bitten by scorpions, and, as a control group, 15 healthy subjects were included in the study. Standard electrocardiograph (ECG) records, 24-hour(More)
Artificial neural network (ANN), pseudo second-order kinetic, and gene expression programming (GEP) models were constructed to predict removal efficiency of Lanaset Red G (LR G) using lentil straw (LS) based on 1152 experimental sets. The sorption process was dependent on adsorbent particle size, pH, initial dye concentration, and contact time. These(More)
Existing literature proves that Optimization via Simulation (OvS) is relatively easy to develop regardless of the complexity of the problem and provide a much more realistic solution methodology without assumption. Hence, we used OvS to determine optimal (R, s, S) policy for Distribution Center (DC)s and suppliers and to properly select the suppliers for(More)
A three-layer artificial neural network (ANN) was constructed to predict the removal efficiency of Lanaset Red (LR) G on Chara contraria based on 2304 experimental sets. The effects of operating variables (particle size, adsorbent dosage, pH regimes, dye concentration, and contact time) were studied to optimize the sorption conditions of this dye. The(More)
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