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- James R. Luedtke, Mahdi Namazifar, Jeff T. Linderoth
- Math. Program.
- 2012

We study approaches for obtaining convex relaxations of global optimization problems containing multilinear functions. Specifically, we compare the concave and convex envelopes of these functions with the relaxations that are obtained with a standard relaxation approach, due to McCormick. The standard approach reformulates the problem to contain only… (More)

- M. Norouzi, A. Karambakhsh, M. Namazifar, B. Savkovic
- 2009 IEEE International Conference on Control and…
- 2009

One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding obstacles especially in crowded and unknown environment. The path followed by a mobile robot and its behavior plays an important role in the quality of localization and mapping as well. To combat this problem, we introduced a real time and robust… (More)

- Pietro Belotti, Andrew J. Miller, Mahdi Namazifar
- Electronic Notes in Discrete Mathematics
- 2010

We study the convex hull of the bounded, nonconvex set M n = { n + 1} for any n ≥ 2. We seek to derive strong valid linear inequalities for M n ; this is motivated by the fact that many exact solvers for nonconvex problems use polyhedral relaxations so as to compute a lower bound via linear programming solvers. We present a class of linear inequalities… (More)

- Mahdi Namazifar, Andrew J. Miller
- CPAIOR
- 2008

Pivot-and-Fix, a new primal heuristic for finding feasible solutions for mixed integer programming (MIP) problems is presented in this paper. Pivot-and-Fixtries to explore potentially promising extreme points of the polyhedron of the problem and by forming smaller serach trees looks for integer feasible solutions. Computational results show that this… (More)

- M. Namazifar, H. Javaheri Neyestanaki
- 2005

In this paper we are about to modify the fuzzy c-mean (FCM) algorithm in a way which this algorithm be able to handle the cases in which the data set is multidimensional, and dimensions are not of equal degree of importance. In such cases, clusters obtained by FCM are not logically satisfying. So some modifications are absolutely needed.

- MAHDI NAMAZIFAR, MOHAMMADREZA RAZZAZI, JAVAHERI NEYESTANAKI
- 2005

Solving fuzzy optimization problems is more complex than solving crisp ones. The complexity of such problems motivates the use of approximation methods to solve them. In this paper, a simulated annealing technique is presented which is able to approximately solve fuzzy optimization problems.

We propose an algorithm for generating feasible solutions to general mixed-integer programming problems. Computational results demonstrating the effectiveness of the heuristic are given. The source code is available as a heuristic in the COIN-OR Branch Cut Solver at www.coin-or.org

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