توازن میان توابع هدف در بهینه‌سازی چندهدفه یکی از ابزارهای تفسیر و بررسی جواب‌های کارا است. جواب‌های کارای سره یکی از مفاهیم مهم از نظر تئوری و عملی می‌باشد که نشان دهنده رفتار توابع هدف طی یک فرایند تغییر می باشد؛ جواب-های کارای سره جواب های کارایی هستند که ناهنجاری های توابع هدف در بعضی از نقاط را فیلتر می کنند و این به تصمیم گیری برای به دست آوردن جواب های با اهمیت بیشتر توسط مدیریت کمک شایانی خواهد کرد. یکی از مهمترین ابزارهای به دست آوردن جواب با توازن کراندار در بهینه سازی چندهدفه، روش اسکالرسازی مجموع وزنی است که بسیاری از نویسندگان این نوع از اسکالرسازی را در بهینه سازی تعاملی بررسی کرده اند. این مقاله روشی برای به دست آوردن جواب-های کارای سره نزدیک به نقطه ایدآل با دیدگاه تئوری و تعاملی و با استفاده از اسکالرسازی وزنی ارائه می‌دهد. با توجه به اینکه نزدیکی به نقطه ایدآل می‌تواند یکی از ترجیحات تصمیم گیرنده باشد؛ این روش، ترجیحات تصمیم گیرنده را بدون از دست دادن تئوری در نظر می‌گیرد. بنابراین این مقاله رویکردی برای یافتن جواب های کارای سره نزدیک به نقطه ایدآل ارائه می دهد. تفاصيل المقالة

در برخی از تحقیقات، پژوهشگران به مطالعه و تخمین برخی از پارامترهای تاثیرگذار بر اندازه کارایی از جمله میزان ورودی یا میزان خروجی یک DMU پرداخته‌اند بطوریکه اندازه کارایی حفظ یا به میزان معینی بهبود یابد .این دسته از مسائل تحت عنوان تحلیل پوششی داده‌های معکوس در ادبیات تحلیل عملکرد مورد مطالعه قرار می‌گیرند. این مقاله به مطالعه تحلیل پوششی داده‌های معکوس می‌پردازد. مسئله تخمین ورودی یا خروجی با بهبود در اندازه کارایی واحد، مورد بررسی قرار گرفته است.لذا در این مقاله، با افزایش سطح ورودی‌های نامطلوب وسطح خروجی‌های مطلوب واحدهای تصمیم‌گیری به همراه بهبود در کارایی که مورد نظر تصمیم‌گیرنده می‌باشد، میزان تغییرات سطح ورودی‌های مطلوب و سطح خروجی‌های نامطلوب تخمین زده می‌شود. برای این منظور، با در نظر گرفتن داده‌ها به صورت بازه‌ای، روش DEA ‌معکوس را با استفاده از مدل برنامه‌ریزی خطی چندهدفه (MOLP)، به کار می‌گیریم، به‌طوری که کارایی واحد تحت ارزیابی بهبود پیدا کند. در ادامه با یک مثال کاربردی روش پیشنهادی مورد بحث و بررسی قرار می‌گیرد. تفاصيل المقالة

One of the major concerns of managers in the field of health is the optimal allocation of manpower and resources; So in this study, to the quality of provided services in this area not to be damaged, we have used the data envelopment analysis (DEA) model to determine the efficiency of hospital emergency departments and possible improvements. Traditional DEA models do not seek to reduce undesirable outputs and increase undesirable inputs, so in this study, decision-making units (DMUs) effect on efficiency has also been investigated in addition to determining the efficiency of decision-making units (DMUs) with the presence of some undesirable output components. To do this, first, the set of proper production possibilities has been defined according to the problem assumptions and while examining the performance and ranking with Andersen-Petersen and Super-SBM models, a new method has been provided to determine the unfavorable performance of some output components in decision-making units. We have specified the effect of undesirable output on determining efficiency. We have also provided a real example of 30 hospital emergencies for 5 desirable inputs and 4 desirable outputs and one undesirable output, solved that example, and determined the efficiency score. تفاصيل المقالة

Endogeneity and its impact on estimating economic models can be seen in many economic studies. Data envelopment analysis is one of the most common non-parametric methods in which different axioms are used to estimate the production function (efficient frontier). However, the issue of endogeneity and its impact on estimating the efficient frontier is less considered. Cordero et al (2016) indicated that standard models of data envelopment analysis do not perform well in the presence of positive and high endogeneity. In this article, a model based on relaxing convexity axiom is presented in which the Cobb-Douglas function is considered as a real production function. Then, the efficiency of the proposed model is compared with the standard models of the data envelopment analysis and Cobb-Douglas function under positive and high endogeneity. The results show that the proposed model outperforms the counterparts. In addition, by comparing the models in different modes of return to scale, it is observed that the type of return to scale is also effective in determining the efficiency and efficiency of the proposed model compared to its economic counterpart. تفاصيل المقالة

This paper proposes a DEA-based model for analyze the fuzzy risk in project selection. We used concept semi-variance for measure upper and downside risk and a DEA model for Classification desirable and undesirable risk. Firstly, the proposed model includes new desirable and undesirable risk-return indexes. Thus a novel DEA model is presented for evaluation and Classification desirable and undesirable risks and finally, is extend to fuzzy DEA model for project portfolio selection. An applied example is used to explain the proposed approach and usefulness and applicability of this approach have been illustrated using the 37 available projects. تفاصيل المقالة

One of the major concerns in healthcare management is the optimal allocation of staffing and resources. The global crisis created by the COVID-19 Pandemic has created extreme strains both on the staffing and the resources available to the healthcare systems. It has geometrically added to the number of patients seeking health services. In addition, the Pandemic has dramatically increased the rate of mortality in the hospitals in an unprecedented way. Therefore, in this research, in order not to sacrifice the quality of the services provided, we have used Data Envelopment Analysis (DEA) model to determine the efficiency of the emergency departments in the hospitals and the possible improvements that could be made to them. As traditional DEA models do not seek to reduce the undesirable outputs and increase the undesirable inputs, in addition to determining the efficiency of decision making units (DMU) despite some undesirable input components, the effect of these units on performance is investigated. To this end, considering the problem assumptions, first, a set of proper production possibilities is defined. Finally, a new method is introduced to determine the system’s performance in the presence of some undesirable input components. The impact of undesirable components on determining efficiency is specified, and a real example is provided consisting of emergency rooms in 30 hospitals, in which five desirable inputs and four desirable outputs along with one undesirable input are considered. The example is solved using the presented model, and the efficiency scores are determined. تفاصيل المقالة

a b s t r a c tOur main goal in this article is to arrange terminal facilities, place different departments, stores and units in predefined areas in such a way as to minimize the cost of moving customers and transportation staff. Especially in large-scale terminals with several different transport segments, it is important for terminal performance to be close to interactive units. Today, meta-heuristic methods are often used to solve optimization problems such as facility design. in this study; The design of the various units, stores, and rooms of a large-scale real terminal was organized using three meta-heuristic algorithms: Migratory Bird Optimization (MBO), Taboo Search (TS), and Simulated Simulation (SA). The results were compared with the existing terminal design. As a result, MBO and SA metaheuristic algorithms have provided the best results, which improve the efficiency of the existing terminal design to an acceptable level. تفاصيل المقالة

In this paper, a facility location model with fuzzy value parameters based on the meta-heuristic method is investigated and solved. The proposed method and model uses fuzzy values to investigate and solve the problem of location allocation. The hypotheses of the problem in question are considered as fuzzy random variables and the capacity of each facility is assumed to be unlimited. This article covers a modern, nature-inspired method called the whale algorithm and the neighborhood search method. The proposed method and related algorithm are tested with practical optimization problems and modeling problems. To evaluate the efficiency and performance of the proposed method, we apply this method to our location models in which fuzzy coefficients are used. The results of numerical optimization show that the proposed method performs better than conventional methods. تفاصيل المقالة

Abstract: In recent years, Graph Coloring Problem (GCP) is one of the main optimization problems from literature. Many real world problems interacting with changing environments can be modeled by dynamic graphs. Graph vertex coloring with a given number of colors is a well-known and much-studied NP-hard problem. Meta-heuristic algorithms are a good choice to solve GCP because they are suitable for problems with NP-hard complexity. However, in many previously proposed algorithms, there are common problems such as runtime algorithm and low convergence of algorithm. Therefore, in this paper, we propose the Fuzzy Whale Optimization Algorithm (FWOA), a variety of basic Whale Optimization Algorithm (WOA), to improve runtime and convergence of algorithm in the GCP. Since WOA at first was introduced for solving continuous problem, we need a discrete WOA. Hence, to use FWOA to discrete search space, the standard arithmetic operators such as addition, subtraction and multiplication extant in FWOA encircling prey, exploitation phase and exploration phase operators based on distance’s theory needs to be redefined in the discrete space. Parameters p and r, are defined randomly in the WOA algorithm in FWOA algorithm defined as fuzzy and are selected in fuzzy tragedy. A set of graph coloring benchmark problems are solved and their performance are compared with some well-known heuristic search methods. Results illustrate that FWOA algorithm are the original focus of this work and in most cases success rate is nearly 100% and the runtime and convergence algorithm has been improved on some graphs. But as we have illustrated that comparison with other manners, we cannot deduce that our algorithm is the best in all instance of graphs. It can be said that a proposed algorithm is able to compete with other algorithms in this context. Obtained results approved the high performance of proposed method. تفاصيل المقالة