An algorithm for solving linear programming problems whose matrix of coefficients contains a large number of "zero" entries is studied. This algorithm is more useful when it is generated as a sub-program in a real-time program. The singly linked lists for storing only the non-zero entries of the coefficients matrix is used. The modified Revised Simplex Method is also used for solving such probl...

assembly lines are special kinds of production systems which are of great importance in the industrial production of high quantity commodities. in many practical manufacturing systems, configuration of assembly lines is fixed and designing a new line may be incurred huge amount of costs and thereby it is not desirable for practitioners. when some changes related to market demand occur, it is wo...

in this paper, we consider a flow shop scheduling problem with availability constraints (fsspac) for the objective of minimizing the makespan. in such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. we proposed a mixed-integer linear programming (milp) model for this problem which can generate non-permutation schedules. furthermor...

among numerous np-hard problems, the traveling salesman problem (tsp) has been one of the most explored, yet unknown one. even a minor modification changes the problem’s status, calling for a different solution. the generalized traveling salesman problem (gtsp)expands the tsp to a much more complicated form, replacing single nodes with a group or cluster of nodes, where the objective is to fi...

In this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. The steps of this algorithm are designed very efficient. For generating an initial solution, we develop an efficient constructive heuristic by modifying the best known NEH algorithm. Effectiveness of the proposed iterated greedy algorithm is t...

The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony s...

Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces. However, the design of its operators makes it unsuitable for many real-life constrained combinatorial optimization problems which operate on binary space. On the other hand, the quantum inspired evolutionary algorithm (QEA) is ver...

Electric power providing companies has to deliver reliable electric power in quality and at minimum cost for the competition in deregulated environment. To know the power system security and operating state, power flows in lines and bus voltage magnitude and angle are calculated using power flow analysis, and to tune the power system for minimum operating cost while ensure security and reliabil...

Differential evolution algorithm is a heuristic global optimization technique based on population which is easy to understand and implement. In this paper we proposed a classification model base on differential evolution algorithm. The proposed model provides a good practicability and promising future for pattern identification.