Abstract: In this work, by introducing a transformation, the nonlinear Schrodinger equation is converted to an ordinary differential equation (ODE). Then, two nonstandard finite difference (NSFD) schemes are constructed for studying the reduced equation. It is shown that the methods preserve the positivity and boundedness properties of the original equation and are stable conditionally and consistence. Finally, the results of the methods are compared with each other and also with the results of the standard finite difference scheme at some points. The graphs of the errors of numerical solutions for these schemes are plotted and compared with the exact solutions.
Abstract: The existence of a performance evaluation system is inevitable due to the dramatic changes in the business environment. The comprehensive performance evaluation attempts to identify institutional units' potential strength and role in influencing the organizations' performance. This study aims to analyze the performance evaluation according to seven dimensions of the Sink and Tuttle model using data envelopment analysis. The result of the seven dimensions of the Sync-Tuttle model is the creation of a comprehensive performance evaluation system in organizations, which leads to the improvement of organizational performance. The proposed model covers all essential performance indicators and takes steps with more generalizability and more realistic evaluation than other performance evaluation systems. In this research, the performance of eight organizational units of the NIPA Company has been evaluated. A total of seven variables of the Sink-Tuttle model are input, and the performance level of organizational units is the output of the proposed model. Coordination between strategies, organizational learning, and knowledge management is recommended to improve organizational performance. The overlap of the evaluation results in the sink and Tuttle model and the data envelopment analysis indicates the validity of the proposed model.Action in the inefficient units can be taken by implementing training, changing key people, developing a participatory system, establishing a performance evaluation system with appropriate criteria, and developing management based on purpose. The results of the proposed performance evaluation model can be used as the main part of formulating and implementing organizations' policies.
Abstract: Over the last few decades, there has been a dramatic increase in public attention to environmental issues. As a consequence of the growing concerns about environmental quality, climate change, and pollutant emission, which are key elements of sustainable development, one of the main challenges is measuring environmental efficiency. The main purpose of this study is to evaluate the ecological efficiency of countries and rank countries based on data envelopment analysis (DEA) method, considering the favorable and unfavorable outputs (7 inputs and 7 outputs) affecting climate change in 2020 in 176 countries. The units were evaluated by CCR model and Also AP model in order to ranking both efficient units and inefficient units. The results show that the environmental efficiency of the selected countries is 80.60% on average, of which Iran ranks 140th with an efficiency of 0.58 and Iceland, Singapore and Lesotho have the highest environmental efficiency, respectively, as well as Sierra Leon, the Philippines, and Pakistan have the lowest environmental performance, respectively.
Abstract: Reduction of energy intensity through gaining energy efficiency is a global agenda for sustainable development goals. The evidence show that the energy intensities of most energy exporting countries (such as OPEC) have historically been very high compared with energy importing and industrialized economies. Hence, the understanding of the main determinants (or drivers) of energy intensity in energy exporting countries is important for economic researchers and policymakers. Therefore, this paper investigates the role of technology and its components on energy intensity changes in OPEC countries using a DEA-Malmquist over the period of 2000-17. The findings show that technological progress has played a significant role in reducing of energy intensity. Moreover, the results after TFP decomposing using DEA method indicates that the negative effect of technical change on energy intensity is much larger than of the efficiency change effect, Although, the estimated values of these components are is relatively weak. Next, we investigate what is main driving of technological progress in the OPEC countries. The findings imply that trade openness is a main factor to causes to improve the productivity.
Abstract: Project-based organizations in upstream industries hold a large share of national resources and play an important role in the development of a country. Performance evaluation of project-based organizations can help managers to use inputs effectively and smooth their way to achieving goals. There are many qualitative and quantitative indices to performance evaluation of project-based organizations. Efficiency calculation through Data Envelopment Analysis (DEA) is a common index for performance assessment in such firms. In the traditional DEA model crisp data is needed while, in the real world, most of the data are imprecise and uncertain. A major cause of uncertainty related to the non-quantifiable, incomplete, and unachievable information that caused fuzzy logic and fuzzy sets merge in different models like DEA. The main idea of the present study is to combine quantitative and qualitative approaches in performance appraisal to take advantage of both and achieve more accurate results; therefore, in this paper, a hybrid model based on Fuzzy Data Envelopment Analysis (FDEA) and Project Excellence Model (PEM) is proposed for performance evaluation in project-based organizations. First, performance assessment by the PEM model of Fuzzy data is accomplished. Then, implementing Fuzzy DEA into the PEM model is performed in which the inputs and outputs of the FDEA model are the PEM model criteria. The proposed hybrid model is used to evaluate 30 petrochemical companies in Iran. The comparison of the results of both models indicates a correlation coefficient of almost 0.90 at the significance level of 0.01 that shows an appropriate correlation between the two models.
Abstract: This paper study a single machine stochastic scheduling problem based on an Iranian real case study in Saipa company in which the objective is to minimize total completion times and delivery costs. According to existence data sets of this company the processing times follows a Normal distribution and based on the managerial decisions two objectives have to be achieved simultaneously including total completion times and controlling tardiness values so that their values are lower than an specified penalty. So, a Chance Constraint Programming (CCP) approach is employed and a mathematical model is presented. In order to solve the problem a Branch and Bound (B&B) method is used to solve the problem optimally and a Particle Swarm Optimization (PSO) metaheuristic is used to find near optimal solutions for large scales. The results show that using the proposed mathematical model and solution approach, could increase the effectiveness and efficiency of production line as 16 to 40 percent. Computational experiments validate the accuracy of proposed method.
Abstract: The main purpose of this paper is to upgrade and improve inefficient units by common weights obtained from all units studied. In fact, we consider the common weight vector as the direction in which inefficient units rise. The methodology of this research is to consider the semi-essential radial model and we want to use the duality of this model to find the common weights of inputs and outputs, some of which are negative. For this purpose, we present a multi-objective problem of generating common weights and use ideal programming to solve it, which leads to the production of a nonlinear problem, which for this particular problem, by a linearization method, is called We turn a linear programming problem. Since the necessary and sufficient condition for the boundary of the semi-essential radial model in the nature of input (output) is that there is an input (output) with at least one positive value, so we observe this condition here. Finally, we will explain our method with an example and the remarkable thing about the promotion method in the present study is that negative data is promoted and improved as negative data.
Abstract: Data Envelopment Analysis (DEA) is a mathematical technique to assess the performance of Decision Making Units (DMUs) with similar inputs and outputs. The traditional DEA models disregard the internal structure of units and have a “black box” view. Thus, to evaluate the structures with more than one stage, the network DEA (NDEA) models expanded. On the other hand, the dynamic optimization models have been presented to eliminate the limitations of static models in optimization. In the article, for the first time, a systematic approach is used to present a dynamic NDEA with constant inputs and undesirable outputs. First, we used an axiomatic approach in DEA with undesirable output and presented an NDEA model with undesirable output. Then, we extended the proposed approach and presented a dynamic NDEA with undesirable output and a constant input. Afterward, we applied this model to evaluate hospitals’ performance in an experimental study to estimate the efficiency of their dynamic network.
Abstract: 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.
Abstract: This work considered the existence, uniqueness and data dependence of quadrupled fixed point theorems for contractions in metric spaces, equipped with vector-valued metrics whose approach is primarily based on Perov-type fixed point of contractive-type multi-valued mapping in Cauchy spaces. This work obtained results that complement recent and available results in literature.
Abstract: The concept of fixed point is of great interest in mathematics as well as in many areas of applied sciences. Previously, the question of fixed points in partially ordered metric spaces had been studied, and quadrupled fixed point theorem is a continuation of the tripled fixed point theorem. This work presents the stability for quadrupled fixed point iterative procedure with the aid of some mathematical analysis properties, and establishes results for mixed monotone mappings which satisfy its contractive-type conditions. The results of this work extend some of the results in literature.
Abstract: In this research the time M-fractional resonant nonlinear Schrödinger differential equation with different forms of nonlinearities, containing Kerr-law and parabolic-law has been studied. For this objective, the modified Kudryashov method and the sine-Gordon expansion approach have been implemented to retrieve a series of resonant solitons solutions for the abovementioned model. The prospective of the schemes in founding soliton solutions of nonlinear time-fractional equations in the truncated M-fractional derivative sense is confirmed.
Abstract: Nowadays, corporate social responsibility (CSR) has significant roles in airline industry. The purpose of Present paper is to prioritize the factors influencing corporate social responsibility (CSR) in airline industry. Present study prioritizes the factors influencing CSR of Iran airline industry by using criteria importance through inter-criteria correlation (CRITIC) and additive ration assessment Complex proportional assessment (COPRAS) to find the best airline among five Iranian airlines Iran during 2021. Criterion utilize in present research comprised of 15 sub-criterion the results show that the energy consumption is the most influence factor among influence factors and airline 3 obtained the first rank. The present study helps airline managers to improve the performance of CSR by influence factors in airline industry.
Abstract: This paper proposes a centralized network data envelopment analysis model that combines the centralized data envelopment analysis model with possibility of downsizing and two-stage network data envelopment analysis. In the proposed model, this paper also considers the situation in which shared inputs are jointly consumed in each stage. We also assume some outputs can be produced by the first and second stages by using separate inputs. The proposed model is illustrated in an empirical example of twenty sale representatives in two provinces of Golestan and Mazandaran. The results provide valuable information for the centralized decision-maker on how to reallocate resources among the units.
Abstract: 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.
Abstract: Cross-docking is the practice of unloading Coronavirus vaccines from inbound delivery vehicles and loading them directly onto outbound vehicles. Cross-docking can streamline supply chains and help them move Coronavirus vaccines to pharmacies faster and more efficiently by eliminating or minimizing warehouse storage costs, space requirements, and inventory handling. Regarding their short shelf-life, the movement of Coronavirus vaccine to cross-dock and their freight scheduling is of great importance. Achieving the goals of green logistics in order to reduce fuel consumption and emission of pollutants has been considered in this study. Accordingly, the present study developed a mixed-integer linear programming (MILP) model for routing and scheduling of cross-dock and transportation in green reverse logistics network of Coronavirus vaccines. The model was multi-product and multi-level and focused on minimizing the logistics network costs to increase efficiency, reduce fuel consumption and pollution, maximizing the consumption value of delivered Coronavirus vaccines and minimizing risk of injection complication due to Coronavirus vaccines corruption. Considering cost minimization (i.e., earliness and tardiness penalty costs of pharmacies order delivery, cost of fuel consumption and environmental pollution caused by outbound vehicles crossover, the inventory holding costs at the temporary storage area of the cross-dock and costs of crossover and use of outbound vehicles) as well as uncertainty in pharmacies demand for Coronavirus vaccines, the model was an NP-hard problem. In this model, the problem-solving time increased exponentially according to the problem dimensions; hence, this study proposed an efficient method using the NSGA II algorithm.
Abstract: The nature of Data Grids is dynamic. In these systems, data access patterns of users and network latency may change. The system needs to meet data availability reliability. Data replication is a well-known method for improving performance parameters such as data access time, availability, load balancing, and reliability. Here, a novel dynamic algorithm is proposed that uses fuzzy inference systems to manage replication for increasing performance. The proposed algorithm uses a new comprehensive set of decision parameters and fuzzy logic in each phase to reduce the inefficiency caused by wrong decisions in different phases in a practical Grid. The algorithm uses two fuzzy interfere systems to select an appropriate place for new replication and a less valuable file for deleting when storage space is full. It places the new replica in a suitable site where the file could possibly be needed soon with high probability. It also prevents deleting valuable files using a fuzzy valuation function. The algorithm was simulated by the OptorSim simulator. The results demonstrated that the algorithm is more effective than other replication methods in terms of the number of created replications, the percentage of storage used, and the job execution time.
Abstract: We propose a new self-starting sixth-order hybrid block linear multistep method using backward differentiation formula for direct solution of third-order differential equations with either initial conditions or boundary conditions. The method used collocation and interpolation techniques with three off-step points and five-step points, choosing power series as the basis function. The convergence of the method is established, and three numerical experiments of initial and boundary value problems are used to demonstrate the efficiency of the proposed method. The numerical results in Tables and Figures show the efficiency of the method. Furthermore, the numerical method outperformed the results from existing literature in terms of accuracy as evident in the results of absolute errors produced.
Abstract: In this paper, we propose some necessary conditions for convergence of Triple Accelerated Over-Relaxation (TAOR) method with respect to $M-$ coefficient matrices. The theoretical approach for the proofs is analyzed through some standard procedures in the literature. Some numerical experiments are performed to show the efficiency of our approach, and the results obtained compared favourably with those obtained through the existing methods in terms of spectral radii of their iteration matrices.
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