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Showing 2 results for Akbari
Ms. Maryam Akbari-Jafarabadi, Prof. Reza Tavakkoli-Moghaddam, Mr. Mehdi Mahmoodjanloo, Mr. Yaser Rahimi, Volume 6, Issue 2 (9-2015)
Abstract
In general, any system may be at risk in a case of losing the critical facilities by natural disasters or terrorist attacks. This paper focuses on identifying the critical facilities and planning to reduce the effect of this event. A three-level model is suggested in the form of a defender-attacker-defender. It is assumed that the facilities are hierarchical and capable of nesting. Also, the attacker budget for the interdiction and defender budget for fortification is limited. At the first level, a defender locates facilities in order to enhance the system capability with the lowest possible cost and full covering customer demand before any interdiction. The worst-case scenario losses are modeled in the second-level. At the third level, a defender is responsible for satisfying the demand of all customers while minimizing the total transportation and outsourcing costs. We use two different approaches to solve this model. In the first approach, the third level of the presented model is coded in Gams software, its second level is solved by an explicit enumeration method, and the first level is solved by tabu search (TS). In the second approach the first level is solved by the bat algorithm (BA). Finally, the conclusion is provided.
Dr Zohreh Akbari , Dr Zeinab Saeidian, Volume 12, Issue 2 (11-2021)
Abstract
In this paper, a nonmonotone line search strategy is presented for minimization of the locally Lipschitz continuous function. First, the Armijo condition is generalized along a descent direction at the current point. Then, a step length is selected along a descent direction satisfying the generalized Armijo condition. We show that there exists at least one step length satisfying the generalized Armijo condition. Next, the nonmonotone line search algorithm is proposed and its global convergence is proved. Finally, the proposed algorithm is implemented in the MATLAB environment and compared with some methods in the subject literature. It can be seen that the proposed method not only computes the global optimum also reduces the number of function evaluations than the monotone line search method.
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