We consider biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective problems. The rst and second approaches are extensions of the labeling method to solve the single objective problem and the third approach is based on dynamic PROGRAMMING. The labeling methods usually producing several nondominated paths, we propose a fuzzy number ranking method to determine a fuzzy shortest path. Illustrative examples are worked out to show the e ectiveness of our algorithms.

We apply a primal-dual simplex algorithm for solving the biobjective min imum cost-time network flow problem such that the total shipping cost and the total shipping fixed time are considered as the first and second objective functions, respectively. To convert the proposed model into a single-objective parametric one, the weighted sum scalarization technique is commonly used. This problem is a mixed-integer PROGRAMMING, which the decision variables are directly dependent together. Generally, the previous works have consid ered the linear biobjective problem with the traditional network flow con straints, while in this paper, corresponding to each flow variable, a binary variable is defined. These zero-one variables are utilized to describe a fixed shipping time for positive flows. The proposed method is successful in finding all supported efficient solutions of a real numerical example.

This paper considers a biobjective transportation problem with various fuzzy objective functions coefficients. Fuzzy coefficients can be of different types such as triangular, trapezoidal, (semi) L 􀀀 R, or at (semi) L 􀀀 R fuzzy numbers. First, we convert the problem to a parametric interval biobjective transportation problem using-cuts of fuzzy coefficients. Then, we consider a fix-cut and obtain a necessarily weak efficient solution to the yielded interval biobjective program by a new algorithm. It uses basic feasible solutions and the parametric simplex algorithm. Furthermore, we suggest another algorithm for finding a reasonable solution, called -necessarily weak efficient, to the main biobjective transportation problem. To illustrate the validity and performance of the proposed algorithms, we present some numerical examples.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method based on dynamic PROGRAMMING has been used to design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method based on dynamic PROGRAMMING for the stabilizing design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Computational grids have provided the usage of computational distributed resources for computation-intensive applications. The development of programs that use these capabilities is one of the challenging issues for grid computing. In this article, an effort has been made in order to solve this problem by presenting mobile-agent-based parallel PROGRAMMING on the grid. The presentation of this model, which has been materialized by extending Alchemi™ grid infrastructure, adding agent properties and navigational commands that let the user to develop his/her program by using agents’ mobility and communication between them. In order to evaluate the system, algorithm of matrix multiplication as well as algorithm of finding the convex hull of a series of points has been implemented in the mentioned system.

In mammals, the intrauterine condition has an important role in the development of fetal physiological systems in later life. Suboptimal maternal environment can alter the regulatory pathways that determine the normal development of the fetus in utero, which in post-natal life may render the individual more susceptible to cardiovascular or metabolic adult-life diseases. Changes in the intrauterine availability of nutrients, oxygen and hormones can change the fetal tissue developmental regulatory planning, which occurs genomically and non-genomically and can cause permanent structural and functional changes in the systems, leading to diseases in early years of life and those that particularly become overt in adulthood. In this review we take a brief look at the main elements which program the fetal system development and consequently induce a crucial impact on the cardiovascular, nervous and hormonal systems in adulthood.

In this study, we discussed a fuzzy PROGRAMMING approach to bi-level linear PROGRAMMING problems and their application. Bi-level linear PROGRAMMING is characterized as mathematical PROGRAMMING to solve decentralized problems with two decision-makers in the hierarchal organization. They become more important for the contemporary decentralized organization where each unit seeks to optimize its own objective. In addition to this, we have considered Bi-Level Linear PROGRAMMING (BLPP) and applied the Fuzzy Mathematical PROGRAMMING (FMP) approach to get the solution of the system. We have suggested the FMP method for the minimization of the objectives in terms of the linear membership functions. FMP is a supervised search procedure (supervised by the upper Decision Maker (DM)). The upper-level decision-maker provides the preferred values of decision variables under his control (to enable the lower level DM to search for his optimum in a wider feasible space) and the bounds of his objective function (to direct the lower level DM to search for his solutions in the right direction).

There are many cases that a nonlinear fractional PROGRAMMING, generated as a result of studying fractional stochastic PROGRAMMING, must be solved. Sometimes an approximate solution may be sufficient enough to start a new process of calculations. To this end, this author introduces a new linear approximation technique for solving a fractional chance constrained PROGRAMMING (CCP) problem. After introducing the problem, the equivalent deterministic form of the fractional nonlinear PROGRAMMING problem is developed. To solve the problem, a fuzzy goal PROGRAMMING model of the equivalent deterministic form of the fractional chance constrained PROGRAMMING is provided and then the process of defuzzification and linearization of the problem is started. A sample test problem is solved for presentation purposes.

Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems. As a recently emerged field of study and practice, virtual cellular manufacturing (VCM) is of enormous importance as one of the types of CM. One kind of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this study, a biobjective mathematical PROGRAMMING model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations while minimizing the production costs and balancing the cell loads. The proposed mathematical model is solved by multi-choice goal PROGRAMMING (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is reached and some suggestions for future works are offered.