• Macro and micro-geometry parameters are used as decision variables. Study of the impact taking complete transmission by two approaches. The using a genetic algorithm NSGA-II. This study aims to implement multi-objective optimization gear unit in order minimize power loss vibrational excitation generated meshing, via multi-scale approach that extends from contact transmission. All these indica...

Many-objective optimization refers to optimization problems with a number of objectives considerably larger than two or three. In this paper, a study on the performance of the Fast Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) for handling such many-objective optimization problems is presented. In its basic form, the algorithm is not well suited for the handling of a larger number o...

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability acros...

The optimization of infrastructure planning in a multimodal network is defined as a multiobjective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. Decision variables are the location of park and ride facilities, train stations and the frequency of public transport lines. For a case study the Pareto set is estimated b...

The optimal design of a plate-fin recuperator of a 200-kW microturbine was studied in this paper. The exergy efficiency, pressure drop and total cost were selected as the three important objective functions of the recuperator. Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were respectively employed for single-objective and multi-objective optimizations. By opt...

Abstract This work addresses the use of a MO optimization algorithm to deal with reliability problem in order determine redundancy and each component system. Often, these problems are formulated as single-objective mixed variables (real-integer) is subject various design constraints. Classical solution approaches were limited most recent based on nature-inspired algorithms which belong artifici...

This research offers an improved method for the self-organization of a swarm UAVs based on social learning approach. To start, we use three different colonies and best members i.e., unmanned aerial vehicles (UAVs) randomly placed in colonies. study uses max-min ant colony optimization (MMACO) conjunction with mechanism to plan optimized path individual colony. Hereinafter, multi-agent system (M...

Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may...

The thermal aware floor planning for VLSIs and placement optimization of electronic components on printed circuit boards (PCBs) using genetic algorithms (GAs) are well studied. However, there no technical paper component considering the heat smartglasses. In this paper, we propose a method optimizing equipped smartglasses elitist non-dominated sorting algorithm (NSGA-II) resistance circuit. Ele...

this paper proposes a bi-objective model for the facility location problem under a congestion system. the idea of the model is motivated by applications of locating servers in bank automated teller machines (atms), communication networks, and so on. this model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing frame...