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Simplex algorithm for solving constrained linear p
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Application background Realize the simplex algorithm for solving constrained standard linear programming problem, according to the input of the objective function and the constraint conditions to solution to meet the constraints of the optimal solution and the objective function of the maximum value. Key Technology Selecting the base variable, selecting the base variable, the variable of the axis of the shaft, the input variables Float matrix[100][100], x[100]; /* record the total array equation, solution of the array * /Int a[100]; /* record based, non based solutions, 0: based, 1: based * /Int m, N, s, type; /* variable equation, the number of constraints, for the type of maximum and minimum value, the minimum 0: 1: maximum; * /Int , indexe, indexl, indexg, , /* ,,, , */
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Memory allocation and recovery simulation
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Application background Simulation of the 2 memory allocation algorithms: first fit; best fit.Shows the distribution and recovery time after the idle partition chain and memory footprint map, and various statistical algorithm to generate the debris free zone (less than 3 units (unit) free zone) number.2 performance parameters: the number of fragments, the number of the average search free area Key Technology Achieve dynamic memory allocation and recovery, the main consideration is three:First, design a data table that records the use of the memory, which is used to record the area of the spare area and the job occupancy. Free list? ];Second, design of memory allocation algorithm based on the design of the data table;Third, third, the design of the data table based on the design of memory recovery algorithm.
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