Bi-level energy optimization model in smart integrated engineering systems using WSN

TLDR

The study addresses computational optimization challenges, including minimum solution matrices, convex infinite sets from closed intervals, objective‑domain nonlinear problems, and increasing programming complexity with organizational growth. The authors employ a bi‑level linear program grounded in fuzzy relational inequalities, along with multi‑objective optimization and discrete branch‑and‑bound techniques for digital integer linear programming to optimize visible‑light brightness and operating costs of access points. The technique was demonstrated to be practical and successful.

Abstract

Based on fuzzy relational inequality, a bi-level linear programme optimizes the visible light brightness and operating costs of access points in a wireless transmission station system. Consider the first computing problem utilizing a minimum solution matrix. A convex infinite set is generated by a restricted number of closed intervals. Second, computing is an objective-domain nonlinear mathematical optimization problem. A multi-objective optimization problem is used to solve the second programming challenge. The constraint set must be used. Use discrete optimization techniques and branch-and-bound procedures for "digital integer linear programming". Our technique has been shown to be both practical and successful. The programming complexity increases as the organization expands.