cultural algorithm
در نشریات گروه صنایع-
This paper presents a multi-stage model for accurate prediction of demand for dairy products (DDP) by the use of artificial intelligence tools including Multi-Layer Perceptron (MLP), Adaptive-Neural-based Fuzzy Inference System (ANFIS), and Support Vector Regression (SVR). The innovation of this work is the improvement of artificial intelligence tools with various meta-heuristic algorithms including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Invasive Weed Optimization (IWO), and Cultural Algorithm (CA). First, the best combination of factors with can affect the DDP is determined by solving a feature selection optimization problem. Then, the artificial intelligent tools are improved with the goal of making a prediction with minimal error. The results indicate that demographic behavior and inflation rate have the greatest impact on dairy consumption in Iran. Moreover, PSO still exhibits a better performance in feature selection in compare of newcomer meta-heuristic algorithms such as IWO and CA. However, IWO shows the best performance in improving the prediction tools by achieving an error of 0.008 and a coefficient of determination of 95%. The final analysis demonstrates the validity and reliability of the results of the proposed model, as it supports the simultaneous analysis and comparison of the outputs of different tools and methods.Keywords: Multi-layer perceptron, adaptive-neural-based Fuzzy Inference System, Support Vector Regression, Invasive Weed Optimization Algorithm, Cultural Algorithm, Feature selection
-
International Journal of Research in Industrial Engineering, Volume:5 Issue: 1, Autumn 2016, PP 16 -42
This paper is an extension of the well-known vehicle routing problem (VRP) consisting of two stages. The first and second stages deal with the vehicle routing and transportation problems, respectively. Waste collection is one of the applications of the considered problem in a real world situation. A new mathematical model for this type of the problem is presented that minimizes the waste collection cost and decreases the risk posed to the environment for hazardous wastes transportation simultaneously. According to the NP-hard nature of the problem, a new multi-objective hybrid cultural and genetic algorithm (MOHCG) is proposed to obtain Pareto solutions. A straightforward representation for coding the given model is proposed to help us in reducing the computational time. To validate the proposed algorithm, a number of test problems are conducted and the obtained results are compared with the results of the well-known multi-objective evolutionary algorithm, namely non-dominated sorting genetic algorithm (NSGA-II), with respect to some comparison metrics. Finally, the conclusion is provided.
Keywords: Waste collection, transportation vehicle routing, Multi-Objective Optimization, Cultural algorithm
- نتایج بر اساس تاریخ انتشار مرتب شدهاند.
- کلیدواژه مورد نظر شما تنها در فیلد کلیدواژگان مقالات جستجو شدهاست. به منظور حذف نتایج غیر مرتبط، جستجو تنها در مقالات مجلاتی انجام شده که با مجله ماخذ هم موضوع هستند.
- در صورتی که میخواهید جستجو را در همه موضوعات و با شرایط دیگر تکرار کنید به صفحه جستجوی پیشرفته مجلات مراجعه کنید.