Optimization algorithms are techniques for solving optimization problems in different areas. Anyone cannot obtain an optimal, precise, and complete solution as those existed in the universe, whether nature behaviour in living creatures, cosmic systems, or at the level of the mechanism of systems in the human body. One of these systems is the system of regulation blood glucose levels in the human body. This system maintains blood glucose levels in a stable condition without increase or decrease. There are many medical, biochemistry, bionic engineering, and physiology researches that have studied the mechanism of regulation of glucose in the human body and the crystallization of the mechanism in the form of mathematical models, which greatly facilitate understanding the mechanism of pancreas hormones and regulation mechanism. However, there is a lack in researches that demonstrate the sequential integrative processes between three main sub-systems and the parallel integrative processes between components of theses sub-systems for managing blood glucose level. Therefore, this research aims to expand on the field of regulation mechanisms of blood glucose. It covers the mechanism with thirteen models that mathematically clarify the mechanism of components of the blood glucose levels regulation in the human body to understand the divine system in the process of the regulation, which may be inspired to create a general method that used to solve optimization problems.

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This paper intends to formulate a new multi-objective inspired method, called Pancreas Hormones Method (PHM) for solving optimization problems. PHM is a population-based method, which based on biological nature of pancreas hormones in the maintenance of blood glucose level in the human body system. The adaptive blood glucose control system has provided useful alternatives and supplements to the types of optimization problems embodied in distributed systems. In this method, cell absorption of glucose is considered as a candidate solution; this happens when each cells' receptors in the human body bind with insulin granule, which allows utilizing glucose by a cell. The pancreas evaluates the fitness of all solutions by measure blood glucose level (BGL) in each iteration (secretion phases). Insulin granules (molecules) tend to target cells randomly and search for the optimal solutions which can get it by retard BGL to normal range. In each generation of the algorithm, the best solution is which can access the BGL to the balance point, whereas the other solutions are considered as a searcher of the search space. In this paper, PHM designed, and then it validated, tested on the bases of standard benchmarks and compared with the results of some successful algorithms. The results of PHM are promising.