Due to strict competition in the global market for Tourism services and Hotels in the tourism industry and also the importance of satisfying tourists, awareness about the efficiency of hotel for hotel owners and hotel managers is very important. The purpose of this paper is measuring performance of hotels in Crete by using Robust Data Envelopment analysis (RDEA) technique considering uncertain data. The proposed method of this paper develops a RDEA method with the consideration of uncertainty on output parameters. In order to use robust optimization methods in this article, after the introduction of input and output, we calculate the efficiency of 50 luxury hotel in Crete by means of GAMS software. The method is based on the adaption of robust optimization approaches proposed in the literature. Finally, we compare the performance achieved with previous research on these hotels and our results. It is found that the efficiency decreases, but the level of confidence increases. پرونده مقاله

چکیدهامروزه با توجه به نقش خاص هر یک از تسهیلات در زنجیره تامین خون، استقرار این مراکز در مکا نهایمناسب با رعایت معیارهای زیستمحیطی از اهمیت ویژ های برخوردار است. سازمان خون استان البرز، باافزایش جمعیت و گسترش شهرها، همواره به دنبال مکا نیابی مناسب جهت استقرار پایگاههای اهدا بوده استتا علاوه بر ارائه خدمت حداکثری به اهداکنندگان، بتوانند آسیبهای زیس تمحیطی را کاهش دهد. در اینمطالعه، برای مکا نیابی مناسب جهت استقرار پایگاههای اهدای خون، معیارهای زیس تمحیطی در نظ ر گرفتهشده است. هدف این مطالعه تعیین تعداد و محل مناسب قرارگیری پایگاههای اهدای خون در سطح شهر بااستفاده از روش ترکیبی ویکور و مدل برنام هریزی ریاضی است به گونهای که این پایگاهها بیشترین سطحخدم تدهی را داشته باشند .کلما ت کلیدی: پایگاه اهدای خون، معیارهای زیس تمحیطی، ویکور و برنامهریزی ریاضی. پرونده مقاله

Mixed model two-sided assembly lines (MM2SAL) are applied to assemble large product models, which is produced in high-volume. So, the sequence planning of products to reduce cost and increase productivity in this kind of lines is imperative. The presented problem is tackled in two steps. In step 1, a framework is developed to select and prioritize customer orders under the finite capacity of the proposed production system. So, an Analytic Network Process (ANP) procedure is applied to sort customers’ order based on 11 assessment criteria. In step 2, a mathematical model is formulated to determine the best sequence of products to minimize the total utility work cost, total idle cost, tardiness/earliness cost, and total operator error cost. After validation of the presented model using GAMS software, according to the NP-hard nature of this problem, a genetic algorithm (GA) and particle swarm optimization (PSO) are used. The performance of these algorithms are evaluated using some different test problems. The results show that the GA algorithm is better than PSO algorithm. Finally, a sign test for the two metaheuristics and GAMS is designed to display the main statistical differences among them. The results of the sign test reveal GAMS is an appropriate software for solving small-sized problems. Also, GA is better than PSO algorithm for large sized problems in terms of objective function and run time. پرونده مقاله

In healthcare, the Patient Appointment Scheduling (PAS) problem is one of the critical issues in Outpatient Chemotherapy Clinics (OCC). In the wake of this, this paper proposes a novel bi-objective mathematical programming model for solving the PAS problem in OCC. The developed mathematical model is inspired by cellular manufacturing. The first objective function minimizes the completion time of all treatments, and the second objective function maximizes the use of nurses' skills while considering clustered patients about their characteristics. To solve the bi-objective mathematical model, for the first time a hybrid approach based on Torabi-Hassini (TH) and Lagrange method is utilized. The results indicate that an increase in the number of nurses will enhance the treatment completion speed and allocation of nurses’ work skill. On the other hand, an increase in the number of chairs in clinics will decrease the assignments of nurses’ skills priority. The study supports decision makers in considering nurses' skills for the PAS problem. The results also denote the desirability of the proposed model. To validate the proposed model, OCC in Tehran is considered as a case study. Computational results reveal that considering nurses' skills in OCC and using the fuzzy clustering model, as a new method in patient clustering, lead to achieving a desirable and more realistic outcome. پرونده مقاله

This paper proposes a bi-objective model for a green closed-loop supply chain network design. Four levels for forward and five levels for reverse flow were considered, including plants, distribution centers, online retailers, traditional retailers and customers for forward flow and customers, collecting centers, disposal centers, repair centers and plants for the reverse flow. The objectives are minimizing the GHG emission and maximizing profit by considering defective products and a second market for these products. Also, online retailers were considered alongside with traditional ones, since the Covid-19 pandemic has led to increase in the amount of online shopping. GAMS software and the Lpmetric technique were used to solve the model in the small and medium sizes. However, for the large size, we used Grasshopper Optimization Algorithm (GOA) as a meta-heuristic approach since solving the large size problem with GAMS is a complicated and time-consuming process. We provided Numerical and computational results to prove the efficiency and feasibility of the presented model. Finally, the managerial insights and future works were provided. پرونده مقاله