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S. Ketabi,
Volume 20, Issue 1 (7-2001)
Abstract

In this paper the problem of minimum cost communication network design is considered where the costs are piecewise linear concave. Several methods are compared: Simulated Annealing method, a heuristic based on the method proposed by Minoux, and a lagrangian method based on lower bounding procedure.
K. Eshghi and S. Pasalar,
Volume 20, Issue 2 (4-2001)
Abstract

Multicommodity distribution problem is one of the most interesting and useful models in mathematical programming due to its major role in distribution networks. The purpose of this paper is to describe and solve a special class of multicommodity distribution problems in which shipment of a commodity from a plant to a customer would go through different distribution centers. The problem is to determine which distribution centers to use so that all customer demands are satisfied, production capacities are not exceeded, and the total distribution cost is minimized.The proposed problem is formulated as a mixed integer linear program and a solution technique based on tabu search is developed, implemented and successfully applied to the test problems. Keywords: Commodity Distribution Systems, Tabu Search, Mathematical Programming
G. Ghassem-Sani and M. Namazi,
Volume 23, Issue 1 (7-2004)
Abstract

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling means assigning a value to a variable.) Solution to these problems is a set of unique values for variables such that all the problem constraints are satisfied. Several search algorithms have been proposed for solving these problems, some of which reduce the need for backtracking by doing some sort of looking to future, and produce more efficient solutions. These are the so-called Forward Checking (FC), Partially Lookahead (PL), and Fully Lookahead (FL) algorithms. They are different in terms of the amount of looking to the future, number of backtracks that are performed, and the quality of the solution that they find. In this paper, we propose a new search algorithm we call Modified Fully Lookahead (MFL) which is Shown to be more efficient than the original Fully Lookahead algorithm
M. E. Hamedani Golshan, S. A. Arefifar, and Gh. Moslehi,
Volume 25, Issue 1 (7-2006)
Abstract

Introducing distributed generation into a power system can lead to numerous benefits including technical, economic, environmental, etc. To attain these benefits, distributed generators with proper rating should be installed at suitable locations. Given the similar effects of distributed generators and capacitor banks on operation indices of a distribution system, simultaneous assignment of best locations and sizes to both will not only lead to greatest benefits from distributed generators but also to lower reactive power capacity requirements. In this paper, a new combined planning problem involving distributed generation and Volt/VAr control means planning is formulated and solved in which the quantity of distributed generators and reactive power sources are simultaneously assigned to buses in a distribution system. Also tap positions of voltage regulators are computed such that with a given distributed generation under peak load conditions, power losses and the reactive power capacity required are minimized. Like many other problems in power network planning, the problem formulated here is a nonlinear combinatorial one. Hence, we employ the tabu search algorithm to solve the optimization problem. The results from applying the algorithm to distribution networks with 6, 19, and 33 buses are presented and compared with those obtained from employing the second order method.
Gh. Moslehi and H. Ghahar,
Volume 25, Issue 2 (1-2007)
Abstract

This paper deals with resource unconstrained project scheduling problems with the objective of maximizing the net present value (NPV) of project cash flows. Here we present a heuristic algorithm named as differential procedure (Dif_AOA). In order to evaluate the efficiency of this algorithm, networks with node numbers between 10-1000 and network complexity coefficients between 1.3-6.6 have been generated. We have compared both the total time for solving the problem and NPV of the Dif_AOA with those of the recursive search procedure. Computational results show that the Dif_AOA performs very effectively. Extensive analysis have been performed to evaluate the node number, complexity network coefficients(CNC), and deadline.
N. Safaeian Hamzeh Kolaei, M. Miri, M. Rashki,
Volume 35, Issue 2 (2-2017)
Abstract

Weighted Simulation-based Design Method (WSDM) is recently developed as an efficient method for Reliability-
Based Design Optimization (RBDO). Despite simplicity, this method degrades effectiveness to obtain accurate optimum design for
high dimension RBDO. Besides, its application range is restricted to RBDOs including only random design variables. In the
present study, local search strategy is employed to enhance the accuracy of conventional WSDOM, and to reduce the computational cost. Besides, a shifting strategy is proposed to increase the application range of WSDM for handling general RBDO problems. The efficiency of the proposed methods is investigated by solving some structural reliability problems.
Comparisonof the obtained results with exact solutions confirms accuracy and superiority of the proposed method for
solving various engineering problems.


N. Fattahi, M. Reisi-Nafchi, G. Moslehi,
Volume 39, Issue 1 (8-2020)
Abstract

Scheduling in production environments is used as a competitive tool to improve efficiency and respond to customer requests. In this paper, a scheduling problem is investigated in a three-stage flexible flowshop environment with the consideration of blocking and batch processing. This problem has been inspired by the charging and packaging line of a large battery manufacturer. In this environment, the first and third stages involve a single processor machine, and the second one consists of m identical parallel batch processing machines. The objective is to minimize the total weighted tardiness of the received orders.Given the lack of consideration of this problem in the literature, first, a mathematical programming model is presented for the problem. Also, due to the NP-hardness of the problem, a variable neighborhood search algorithm and a memetic algorithm are developed to solve it. The computational results show that the variable neighborhood search algorithm can solve instances up to 1200 orders and 15 machines with an average deviation of about 1.9%, relative to the best solution of the two algorithms, and the memetic algorithm can solve instances up to 1200 orders and 15 machines with an average deviation of about 7.8%, as compared e to the best solution of the two algorithms. In general, computational results show the better performance of the variable neighborhood search algorithm in comparison to the memetic algorithm.
N. Mashhadi Mohammad Reza , H. Omranpour,
Volume 41, Issue 1 (9-2022)
Abstract

One of the most important issues in engineering is to find the optimal global points of the functions used. It is not easy to find such a point in some functions due to the reasons such as large number of dimensions or inability to derive them from the function. Also in engineering modeling, we do not have the relationships of many functions, but we can input and output them as a black box. Therefore, the meta-heuristic algorithms are presented.
In this paper, a meta-heuristic algorithm based on the behavior of vortices in fluid physics is presented. Technically, the algorithm is made up of vortices. Each vortex contains some particles. The particles move by the presented rotation matrix. This movement causes the local search. Also by selecting another vortex through the selection algorithm, each vortex attempts to escape the local optima and reach the global optima. The algorithm will explore and exploit the given function using its operators. Another innovation of this paper is the introduction of two new evaluation criteria for optimization algorithms. These two criteria show the behavior and convergence of algorithms along the way to reach the global optimal point or fall into the local optima. The proposed algorithm has been implemented, evaluated and compared with the numerical optimization state of the art algorithms. It was observed that the proposed method was able to achieve better results than most of the other methods in the major of twenty-four standard functions in different dimensions.  (All codes available at http://web.nit.ac.ir/ h.omranpour/.).

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