Heat loss is a major
challenge in heat transfer problems.
Several
researchers have minimized heat loss for different heat transfer cases,
focusing on one optimization technique; however, not all optimization
techniques are suitable for a given problem. A limited number of studies
have compared different techniques for a given problem under boundary
conditions and constraints. This review revisits basic heat transfer
problems and identifies a promising technique for each problem to
minimize heat loss. The paper considers three techniques: nonlinear
least-squares error (LSE), interior point linear programming (IPLP),
and genetic algorithm. Two cases are studied: 1. heat loss optimization
from cylindrical insulating surfaces and 2. laminar airflow on a heated
plate. The results are compared for each technique, and a suitable
technique is recommended for each considered case. Nonlinear LSE is
found to be most suitable for case 1. IPLP and GA are recommended
for the Case 2 problem. The average thermal conductivity is found
to be 0.081 W/mK. The average insulation thickness is found to be
213.25 mm. This research will act as a basis for future research to
justify and implement suitable techniques for different heat transfer
problems.