Using two-phase evolutionary computation approach for nonlinear constrained signal detectors allocation problems

Using a Hybrid Evolutionary Algorithm for Solving Signal Transmission Station Location and Allocation Problem with Different Regional Communication Quality Restriction

“…The model of the multiple category detector location-allocation problems with a linear resource limitation constraint is considered in this study, and the formulation is modeled as a mixed-integer nonlinear programming problem. In this research, the signal transmission station deployment problem is with "different" regional communication quality restrictions when the problem investigated by Chen et al [8] is only with the "single" regional communication quality restriction. In other words, we extend the problem discussed by Chen et al [8] to be the multiple regions with the corresponding communication quality requirement.…”

“…For most realistic applications, the function can be considered as a monotonically decreasing function to the distance. By getting the distance d and signal decay exponent s of detector type i, the signal decay function [5,8] can be described as:…”

“…Assume the probability that a communication event occurring at location X k which is not served by all the signal transmission stations is formulated [5,8] as:…”

“…The multiple detector problems in their study appear to p-center problems [6] while one detector location problem looks like a 1-center or minimax single facility location problem [7]. Chen et al [8] extended their study into nonlinearly constrained various signal detector location-allocation problems; the categories of detectors and the corresponding amount and positions were decided simultaneously. In the problem model, the detection signal strength of the detector declines as the detection distance increases.…”

“…However, these heuristic methods cannot ensure to provide the optimal solution(s). In this study, we proposed a hybrid evolutionary computation approach that mixes IA and PSO instead of using the two-phase approach of using IA and PSO [8,17]. The design of the proposed approach uses IA to decide the number of the signal transmission stations and the category of each station simultaneously, and then uses PSO to find the optimal locations for all the stations provided by IA.…”