In the last decade, theory of constraint application in project management lead to make a new approach for project scheduling and control as a critical chain. In this paper, a multi-objective optimization model for multi-project scheduling on critical chain is investigated. The objectives include time, cost and quality. In order to solve the problem, a Simulated Annealing algorithm is developed...

This article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. The objective is to minimize the makespan for a given set of jobs in the system. This problem class is NP-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. A number of test problems are randomly ge...

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...

Hand gesture recognition is very important to communicate in sign language. In this paper, an effective object tracking and hand gesture recognition method is proposed. This method is combination of two well-known approaches, the mean shift and the motion detection algorithm. The mean shift algorithm can track objects based on the color, then when hand passes the face occlusion happens. Several...

in this paper, we deal to obtain some new complexity results for solving semidefinite optimization (sdo) problem by interior-point methods (ipms). we define a new proximity function for the sdo by a new kernel function. furthermore we formulate an algorithm for a primal dual interior-point method (ipm) for the sdo by using the proximity function and give its complexity analysis, and then we sho...

This paper proposes improvements and revisions to a recent approach in a voting system, and provides an effective approach with a stronger discriminate power. For this purpose, the advantage of a linear transformation is utilized to redene a previously used concept of virtual worst candidate, by incorporating the existing weight restrictions. Then, the best score of this virtual candidate is us...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...