Showing 4 results for Mathematical Programming
R. Ramezanian, M.b. Aryanezhad , M. Heydari,
Volume 21, Issue 2 (5-2010)
Abstract
In this paper, we consider a flow shop scheduling problem with bypass consideration for minimizing the sum of earliness and tardiness costs. We propose a new mathematical modeling to formulate this problem. There are several constraints which are involved in our modeling such as the due date of jobs, the job ready times, the earliness and the tardiness cost of jobs, and so on. We apply adapted genetic algorithm based on bypass consideration to solve the problem. The basic parameters of this meta-heuristic are briefly discussed in this paper. Also a computational experiment is conducted to evaluate the performance of the implemented methods. The implemented algorithm can be used to solve large scale flow shop scheduling problem with bypass effectively .
Mahdi Karbasian, Saeed Abedi,
Volume 23, Issue 1 (3-2012)
Abstract
One of the main principles of the passive defense is the principle of site selection. In this paper, we propose a multiple objective nonlinear programming model that considers the principle of the site selection in terms of two qualitative and quantitative aspects. The purpose of the proposed model is selection of the place of key production facilities of a system in which not only it observes the dispersion principle but also reduces the system transportation costs. Moreover, the proposed model tries to select the sites that can fulfill other elements of site selection as well as dispersion in a way that it increases the trustworthiness of the selected network. For solving the proposed model we used the Genetic Algorithm integrated with TOPSIS method.
Dr. Amin Vahidi, Dr. Alireza Aliahmadi, Dr. Mohammad Reza Hamidi, Dr. Ehsan Jahani,
Volume 26, Issue 3 (9-2015)
Abstract
This paper offers an approach that could be useful for diverse types of layout problems or even area allocation problems. By this approach there is no need to large number of discrete variables and only by few continues variables large-scale layout problems could be solved in polynomial time. This is resulted from dividing area into discrete and continuous dimensions. Also defining decision variables as starting and finishing point of departments in area makes it possible to model layout problem so. This paper also provides new technique that models basic constraints of layout problems.
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Sima Boosaiedi, Mohammad Reisi-Nafchi, Ghasem Moslehi,
Volume 33, Issue 2 (6-2022)
Abstract
Operating rooms have become the most important areas in hospitals because of the scarcity and cost of resources. The present study investigates operating room scheduling and rescheduling considering the priority of surgical patients in a specialized hospital. The ultimate purpose of scheduling is to minimize patient waiting time, surgeon idle time between surgeries, and penalties for deviations from operating room preferences. A mathematical programming model is presented to solve the problem. Because the problem is strongly NP-hard, two heuristic algorithms are presented. A heuristic algorithm based on a mathematical programming model with local search obtains near-optimal solutions for all the samples. The average relative deviation of this algorithm is 0.02%. In continuous, heuristic algorithms performance have been investigated by increasing the number of patients and reduce the number of recovery beds. Next, a rescheduling heuristic algorithm is presented to deal with real-time situations. This algorithm presents fewer changes resulting from rescheduling in comparison with the scheduling problem.
