Research Paper
Metaheuristics Algorithms
fatemeh sogandi
Abstract
Curve fitting is a computational problem in which we look for a base objective function with a set of data points. Recently, nonparametric regression has received a lot of attention from researchers. Usually, spline functions are used due to the difficulty of the curve fitting. In this regard, the choice ...
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Curve fitting is a computational problem in which we look for a base objective function with a set of data points. Recently, nonparametric regression has received a lot of attention from researchers. Usually, spline functions are used due to the difficulty of the curve fitting. In this regard, the choice of the number and location of knots for regression is a major issue. Therefore, in this study, a Genetic algorithm simultaneously determines the number and location of the knots based on two criteria comprise of least square error and capability process index. The proposed algorithm performance has been evaluated by some numerical examples. Simulation results and comparisons reveal that the proposed approach in curve fitting has satisfactory performance. Also, a sensitivity analysis on the number of knots has been illustrated by an example. Finally, simulation results from a real case in statistical process control show that the proposed Genetic algorithm works well in practice.
Research Paper
Engineering Optimization
Parviz Tohidi Nasab; Mohsen Vaez Ghasemi; Ghasem Tohidi
Abstract
The Aircraft Scheduling Problem (ASP) refers to allocating each aircraft to the optimal take-off and landing time and the appropriate runway. This problem is the allocation of aircraft to the desired runway so that the total damage due to delays or haste in landing or take-off of all aircraft is minimized. ...
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The Aircraft Scheduling Problem (ASP) refers to allocating each aircraft to the optimal take-off and landing time and the appropriate runway. This problem is the allocation of aircraft to the desired runway so that the total damage due to delays or haste in landing or take-off of all aircraft is minimized. Runway allocation, landing and take-off sequences, and scheduling for each aircraft must be done in a predetermined time window. Time should also be considered as the time of separation between landings and take-offs due to the wake vortex phenomenon. In general, the purpose of such problems is to make maximum use of the runway. Therefore, in this study, a mathematical model of robust landing and take-off scheduling at an airport is provided, assuming no access to the airport runway at certain times. Moreover, delays and haste in landing and take-off on the runway, limited access to aircraft, runway repair time, and the possibility of runway disturbances are investigated. Robust optimization is used to deal with uncertainty at take-off and landing times. Finally, Genetic and Imperialistic Competitive Algorithm are used to evaluate and analyze the problem because it is NP-HARD problem. The results indicate the ability of the proposed algorithms to find high-quality solutions in a short computation time for problems up to 7 runways and 60 aircraft.
Research Paper
Sustainable development
mohammad reza zahedi; shayan naghdi khanachah; Mostafa zahedi
Abstract
Improving supply chain management performance is one of the key issues for companies to gain competitive advantage. In this regard, one of the solutions is a pure approach. A lean approach helps eliminate supply chain waste. On the other hand, based on the conditions of Iran and the existence of abundant ...
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Improving supply chain management performance is one of the key issues for companies to gain competitive advantage. In this regard, one of the solutions is a pure approach. A lean approach helps eliminate supply chain waste. On the other hand, based on the conditions of Iran and the existence of abundant auto parts industry, the implementation of a lean approach in the supply chain of organizations operating in this field, is extremely important in order to conduct this study in one of the largest companies Activities in the automotive parts industry have been implemented. At first, by reviewing the literature, eight key factors that cause the supply chain to be clean were identified, and 40 supply chain experts were assisted using a questionnaire. The normality of the data distribution was examined using the Kolmogorov-Smirnov test. The main result of this study was the pattern of factors affecting the purity of the supply chain in the automotive parts industry. This model includes the leveling of factors affecting the supply chain, which provides managers with a comprehensive view and attitude about the relationships between these variables.
