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<p>In this paper, interval linear fractional programming (ILFP) problem, as a special model of mathematical programming, is considered. So far, few methods have been proposed to determine optimal value of the objective function of the ILFP, but there is no method to obtain optimal solution (OS) for the decision variables. In this paper, two new methods are suggested to obtain the OS of the ILFP including the linear fractional optimal solution (LFOS) and improved linear fractional optimal solution (ILFOS). In the LFOS method, it is possible that some points of the obtained region do not satisfy the largest space. Thus, by adding some supplementary constraints, the ILFOS method is proposed. Therefore, the infeasible part of the region in the LFOS method is removed. Using the proposed methods, several numerical examples are solved. Monte Carlo simulation is used to analyse the numerical results. We use our methods for solving an ILFP model related to the facilities allocation of a bank to persons in different economic sections.</p>

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Linear fractional programming problems in an interval environment

  • 期刊论文

  • 发表日期：

    2026年3月16日

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  • Fatemeh Salary PourSharif Abad,
  • Mehdi Allahdadi

摘要

In this paper, interval linear fractional programming (ILFP) problem, as a special model of mathematical programming, is considered. So far, few methods have been proposed to determine optimal value of the objective function of the ILFP, but there is no method to obtain optimal solution (OS) for the decision variables. In this paper, two new methods are suggested to obtain the OS of the ILFP including the linear fractional optimal solution (LFOS) and improved linear fractional optimal solution (ILFOS). In the LFOS method, it is possible that some points of the obtained region do not satisfy the largest space. Thus, by adding some supplementary constraints, the ILFOS method is proposed. Therefore, the infeasible part of the region in the LFOS method is removed. Using the proposed methods, several numerical examples are solved. Monte Carlo simulation is used to analyse the numerical results. We use our methods for solving an ILFP model related to the facilities allocation of a bank to persons in different economic sections.