Introduction: Water quality protection along rivers involves water quality monitoring and assessment, establishing water quality goals, and controlling pollutant discharges, so that an acceptable level of water quality is maintained.The control of water quality at various locations along a river requires determining the optimal pollutant removal levels at point and nonpoint pollution sources that would yield a satisfactory water quality response in a cost-effective, equitable, and efficient manner (Burn and McBean 1985; Burn and Yulianti 2001). This is known as the “Optimal Waste Load Allocation.” Typical multi objective optimal waste load allocation problems address minimization of the total treatment cost and minimization of the inequity among the pollutant dischargers, subject to constraints on satisfaction of a specified dissolved oxygen (DO) standard at all the check points along the river (Burn and Yulianti 2001). In this research, the capability of Multi objective Ant Colony Optimization Algorithm is applied to a multi objective waste load allocation problem.

This paper presents a multiobjective power control Algorithm that updates the transmitted power based on local information. The proposed Algorithm is expanded by using multiobjective optimization schemes. The objectives to be optimized in this paper are determined so as to reduce the SINR fluctuations as well as maintaining the SINR to an acceptable level with minimizing an average transmitted power. The convergence properties of the proposed Algorithm are studied theoretically and with numerical simulations. The results indicate that the Algorithm converges more rapidly and has lower average transmitted power than other existing Algorithms. The current study also suggests a practical version of the proposed Algorithm and compares it to the existing totally distributed bang-bang power control (B-BPC) or fixed step power control (FSPC) and multiobjective totally distributed power control (MOTDPC) Algorithms. Numerical results show that the proposed Algorithm is potentially much more efficient in terms of convergence speed and average consumption power than the other two Algorithms.

Bone drilling process is one of the most common processes in the orthopedic surgeries and bone break treatments. It is also very frequent in dentistry and bone sampling operations. Bone is a complex material and the machining process itself is sensitive, so bone drilling is one of the most important, common and sensitive processes in Biomedical Engineering field. Orthopedic surgeries can be improved using robotic bone drilling systems and mechatronic bone drilling tools. In the present study, multiobjective optimization is performed on the temperature and trust force at two steps. At the first step, two regression models are developed for modeling the temperature and force in bone drilling process considering three design variables, namely tool’ s rotational speed (V), feed rate (f) and tool diameter (D). At the second step, using the regression models, Multi-objective genetic Algorithm is used for the Pareto based optimization of bone drilling process considering two conflicting objectives: temperature and force. It has been found out that there are considerable connections and feasible principles for an optimal design of the process in case of applying Pareto-based Multi-objective optimization; otherwise, these interesting results would not be discernible.

In this paper, a new approach to optimize an Autonomous Underwater Vehicle (AUV) hull geometry is presented. Using this methode, the nose and tail of an underwater vehicle are designed, such that their length constraints due to the arrangement of different components in the AUV body are properly addressed. In the current study, an optimal design for the body profile of a torpedo-shaped AUV is conducted, and a Multi-objective optimization scheme based on the optimization Algorithm Nondominated Sorting Genetic Algorithm-II (NSGA-II), as an evolutionary Algorithm is employed. In addition, predefined geometrical constraints were considered so that equipment with the specific dimensions can be placed inside the AUV space without any effect on the AUV volume and the wetted surface. By optimizing the parameters of the newly presented profile, in addition to maximizing the volume and minimizing the wetted surface area, more diversed shapes can be achieved than with the ‘ Myring’ profile. A CFD analysis of the final optimal design indicates that with the help of the proposed profile, the hydrodynamic parameters for the AUV hull were effectively improved.