Abstract
We consider a multi-extreme placement problem with a nonlinear goal function and linear constraints. The upwardly convex original goal function is replaced by a piecewise linear function, and the original problem is reduced to a partial-integer approximate problem. To solve the approximate problem, we propose a two-way iterative method for determining the plan that is close to the optimal plan. At each iteration, transport problems are solved and the locally optimal solution of the original problem is determined. Using the obtained locally optimal solution of the approximate problem, it is possible to implement a two-way coordinate narrowing of the area of acceptable solutions to the original problem. Using the optimal solution to the problem of placement with limited capacities, the range of acceptable solutions to the problem of placement with capacity restrictions in the variant formulation is narrowed. We define a plan that belonged to a new domain obtained by excluding some non-optimal plans from the set of acceptable solutions, which provides a minimum of the objective function of the original problem. The value of the objective function corresponding to the obtained solution is evaluated from below. The article describes the algorithm for solving the placement problem and analyzes the effectiveness of the method based on experimental calculations.
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