Academic Platform Journal of Engineering and Smart Systems最新文献

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Synchronization of Incommensurate Fractional-order King Cobra Chaotic System 非相称分数阶眼镜蛇王混沌系统的同步

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1350442

Haris ÇALGAN, Abdullah GÖKYILDIRIM

引用次数: 0

Tabu Search with Variable Neighborhood Search Algorithm for Home Healthcare Routing Problem for Multiple Hospitals with Balanced Workload 基于可变邻域搜索算法的多医院负载均衡家庭医疗路径问题

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-09-30 DOI: 10.21541/apjess.1255522

Gülçin DİNÇ YALÇIN, Tuğçe YAVUZ, Şüheda ALTINTAŞ

{"title":"Tabu Search with Variable Neighborhood Search Algorithm for Home Healthcare Routing Problem for Multiple Hospitals with Balanced Workload","authors":"Gülçin DİNÇ YALÇIN, Tuğçe YAVUZ, Şüheda ALTINTAŞ","doi":"10.21541/apjess.1255522","DOIUrl":"https://doi.org/10.21541/apjess.1255522","url":null,"abstract":"In this paper, we study home healthcare routing and scheduling problem where multiple hospitals serve patients. In the public hospitals in healthcare system of Türkiye, patients requiring home healthcare are assigned to the hospital that serves their place of residence. This can cause the workload of hospitals to become unbalanced in terms of the time needed for both traveling and operation. The aim of this paper is to generate routes with a balanced workload for hospitals, giving consideration to the time windows of patients and the working hours of health workers. Firstly, we construct a mathematical model which can solve toy and small-scale problems whilst taking into account the importance of a balanced workload. Then, a Tabu Search with a Variable Neighborhood Search (TS-VNS) algorithm is developed to solve large-scale problems. The performance of the TS-VNS algorithm is tested by comparing the results of the mathematical model with the generated test problems at a small scale. Additionally, large-scale test problems from the literature are sourced for the problem and solved by the TS-VNS algorithm. The results demonstrate the efficiency of the TS-VNS algorithm.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136271945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Unconfined Compressive Strength of Microfine Cement Injected Sands Using Fuzzy Logic Method 应用模糊逻辑方法预测微细水泥注入砂的无侧限抗压强度

Academic Platform Journal of Engineering and Smart Systems Pub Date : 2023-05-18 DOI: 10.21541/apjess.1223846

Eray YILDIRIM, Eyubhan AVCI, Nurten AKGÜN TANBAY

{"title":"Prediction of Unconfined Compressive Strength of Microfine Cement Injected Sands Using Fuzzy Logic Method","authors":"Eray YILDIRIM, Eyubhan AVCI, Nurten AKGÜN TANBAY","doi":"10.21541/apjess.1223846","DOIUrl":"https://doi.org/10.21541/apjess.1223846","url":null,"abstract":"In this study, unconfined compressive strength values of sand soil injected with microfine cement were predicted using fuzzy logic method. Mamdani and Sugeno methods were applied in the fuzzy logic models. In addition, a regression analysis was carried out in order to compare these two methods. In the models, water/cement ratio and injection pressure were the input variables, and unconfined compressive strength was the output variable. The dataset includes 427 samples, which were experimentally injected with microfine cement. Predictions for unconfined compressive strength were obtained by creating membership functions and rule base for each input (predictive) parameter in fuzzy logic models. The coefficient of determination (R2) and Mean Square Error (MSE) were used as criteria for evaluating the performance of the developed models. The results suggested that the three applied models (i.e. Mamdani, Sugeno and regression) provided statistically significant results, and these methods could be used in the future prediction-based studies. The results showed that Sugeno model provided the best performance for predicting unconfined compressive strength. It was followed by Mamdani and Regression models, respectively. This study has suggested that the fuzzy logic method can be an alternative to the regression method which traditionally has been used in prediction process.","PeriodicalId":472387,"journal":{"name":"Academic Platform Journal of Engineering and Smart Systems","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135717751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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