This study focused on the expansion planning optimization of energy systems employing two forms of energy: the expansion of electrical and thermal energies simultaneously. The main objective of this investigation is confirming network adequacy by adding new equipment to the network, over a given planning horizon. The main objective of the energy expansion planning (EEP) is to minimize the real energy loss, voltage deviation and the total cost of installation equipments. Since the objectives are different and incommensurable, it is difficult to solve the problem by the conventional approaches that may optimize a single objective. So, the meta-heuristic algorithm is applied to this problem. Here, Honey Bee Mating Optimization algorithm (HBMO) as a new evolutionary optimization algorithm is utilized. In order to improve the total ability of HBMO for the global search and exploration, a new modification process is suggested such a way that the algorithm will search the total search space globally. Also, regarding the uncertainties of the new complicated energy systems, in this paper for the first time, the EEP problem is investigated in a stochastic environment by the use of probabilistic load flow technique based on Point Estimate Method (PEM). In order to evaluate the feasibility and effectiveness of the proposed algorithm, two modified test systems are used as case studies. (C) 2014 Elsevier Ltd. All rights reserved.