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Open Access Article
1 - A BACKWARD DIFFERENTIATION FORMULA FOR THIRD-ORDER INITIAL OR BOUNDARY VALUES PROBLEMS USING COLLOCATION METHOD
GAFAR TIAMIYU Abosede COLE KHADEEJAH AUDUWe 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 interp MoreWe 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. Manuscript profile -
Open Access Article
2 - Convergence of Triple Accelerated Over-Relaxation (TAOR) Method for M-Matrix Linear Systems
KHADEEJAH AUDU Yusuph Yahaya Rufus Adeboye Usman AbubakarIn 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. Som MoreIn 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. Manuscript profile -
Open Access Article
3 - Centralized resource allocation with the possibility of downsizing to evaluate two-stage production system with shared inputs
Amir Yadollahi رضا کاظمی متین Farhad Hosseinzadeh LotfiThis 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 s MoreThis 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. Manuscript profile -
Open Access Article
4 - A new method for solving of the Graph Coloring Problem based on a fuzzy logic and whale optimization algorithm
طاها مصطفایی فرزین مدرس خیابانی نیما جعفری نویمی پور بهروز دانشیانAbstract: 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 w MoreAbstract: 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. Manuscript profile -
Open Access Article
5 - Presenting a Mathematical Programming Model for Routing and Scheduling of Cross-Dock and Transportation in Green Reverse Logistics Network of COVID-19 Vaccines
Pezhman Abbasi Tavallali محمدرضا فیلی زاده Atefeh AmindoustCross-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 MoreCross-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. Manuscript profile -
Open Access Article
6 - Minimizing job execution time in Data Grid by A fuzzy dynamic replication algorithm
مهسا بیگرضایی سید لیلی میر طاهری mirtaheriThe 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 MoreThe 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. Manuscript profile
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