Solving method of mixed integer linear programming model

Abstract

The invention provides a solving method of a mixed integer linear programming model. The solving method includes the steps of 1, solving an integer-constraint-free linear programming model by the simplex method to obtain a group of integer-constraint-free optimal solutions; 2, separating solutions of integer-constrained decision variables from the obtained optimal solutions, and directly valuing the solutions with integer values the nearest to the obtained optimal solutions; 3, integrally removing the integer-constrained decision variables and their constraints from the mixed integer linear programming model to obtain a linear programming model with the integer-constrained decision variables removed; 4, solving the integer-constraint-free linear programming model by the simplex method to obtain a group of non-integer solutions; 5, combining the integer solutions and the non-integer solutions to obtain near-optimal solutions to the mixed integer linear programming model. The method employing two-phase solving allows the mixed integer linear programing model to be quickly solved and results to be quickly output, the output results are accurate, and calculation efficiency is improved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a solution method for a mixed integer linear programming model. Background technique [0002] Different from the linear programming model of general procurement plan, in addition to the basic constraints such as procurement weight and procurement funds, the coal procurement plan also includes coal quality constraints such as coal calorific value, coal Vdaf, and coal Std, and generally requires the purchase of coal sources for railway transportation The amount is an integer multiple of the coal loading amount of a single compartment. Combining such characteristics, the linear programming model of coal purchase plan is a mixed integer linear programming model. [0003] At present, the solution algorithms of the mixed integer linear programming model mainly include two types: exact algorithm and heuristic algorithm. The exact algorithm includes branch and bound method, column gen...

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Problems solved by technology

[0004] Among them, the exact algorithm can obtain the exact optimal solution of the model, but its disadvantage is that under the existing computer technology, the problem with many decision variables cannot be dealt with within a limited calculation time.

Although the heuristic algorithm can deal with problems with many decision variables, the optimal solution it obtains is an approximate optimal solution, and it is easy to fall into a local optimal solution. The difference between the approximate optimal solution obtained and the actual optimal solution is The gap between cannot be measured and estimated

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