Authors

Interval method of target solution displacement and its application in situational planning

In the Interval Method of Target Solution Displacement the problem formulation can be refined by an expert at any step of the interactive solution search process, based on the analysis of intermediate results and situation portraits (target, current, and achieved). The best approximation to a feasible solution can be found even with an inconsistent system of constraints. At all stages of computation, IMTSD operates not with boundaries but with real-number segments as integral objects. IMTSD allows the integration of domain expert knowledge (represented in the form of mandatory and guiding requirements for the solution) with a formalized step-by-step search for feasible solutions. The step-by-step human-in-the-loop solution search scheme enables the expert (or an intelligent robot) to: analyse constraint violations; evaluate the feasibility and effectiveness of solutions; input directives that guide the search (“increase”, “decrease”, “fix” the right-hand sides of selected constraints); adjust the priorities of selected constraints and the levels of applied data and solution precision; modify the problem formulation by adding/removing constraints, changing the number of main variables, and updating constraint coefficients. Numerical experiments have demonstrated the high efficiency of IMTSD in solving complex situational planning problems under uncertainty. An example of using IMTSD to solve the resource allocation problem in emergency situation is presented. IMTSD is considered as a contribution to the methodological arsenal of technologies for solving practically significant linear situational planning problems. Read more...