This paper introduces an effective method by combining the multi-objective technique with bird swarm algorithm (BSA) to obtain a new called MBSA. The MBSA obtains some of different non-dominated techniques that maintain variety amongst optimal solutions. To verify and evaluate effectiveness MBSA, collections constrained, unconstrained, engineering problems are measured. These have various Paret...

in this paper a non linear integrated fuzzy multi-objective production planning model with the labor learning and machines deterioration effects is presented. the objective function consists of two quantitative objectives namely increase profits and reduces the cost of system failure and a qualitative objective namely increases the satisfaction rate of the customers. different weights for objec...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

this study is focused on developing an integrated optimization-simulation based genetic algorithm model (iosga) to develop the operational policies for a multi-purpose reservoir system. the objective function of the optimization model is considered to be a linear function of reliability (rel), resiliency (res), and vulnerability (vul) of the river-reservoir system. genetic algorithm (ga) is emp...

Many-objective optimization problems (MaOPs) are challenging in scientific research. Research has tended to focus on algorithms rather than algorithm frameworks. In this paper, we introduce a projection-based evolutionary algorithm, MOEA/PII. Applying the idea of dimension reduction and decomposition, it divides objective space into projection plane free dimension(s). The balance between conver...

Multi-objective genetic algorithms (GAs) are used for Pareto approach optimization of thermodynamic cycle of ideal turbojet engines. On this behalf, a new diversity preserving algorithm is proposed to enhance the performance of multi-objective evolutionary algorithms (MOEAs) in optimization problems with more than two objective functions. The important conflicting thermodynamic objectives that ...