It is a known fact that the performance of optimization algorithms for NP-Hard problems vary from instance to instance. We observed the same trend when we comprehensively studied multiobjective evolutionary algorithms (MOEAs) on a six benchmark instances of discrete time-cost trade-off problem (DTCTP) in a construction project. In this paper, instead of using a single algorithm to solve DTCTP, ...

In Wireless Sensor Network (WSN), coverage and connectivity are the vital challenges in target-based region. The linear objective is to find positions cover complete target nodes between each sensor for data forwarding towards base station given a grid with points potential placement position. this paper, multiobjective problem on WSN (t-WSN) derived, which minimizes number of deployed n...

Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity, effectiveness and minimum involvement of the user. This article develops a multi-objective variation of the Nelder-Mead simplex method and combines it with NSGA-II in order to improve the quality and spread of the solutio...

A kind of unrelated parallel machines scheduling problem is discussed. The memberships of fuzzy due dates denote the grades of satisfaction with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Two kind of genetic algorithms are employed to search optimal solution set of the problem. Bo...

A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...

In this article, the multi-objective optimization of cylindrical aluminum tubes under axial impact load is presented.The absorbed energy and the specific absorbed energy (SEA) are considered as objective functions while the maximum crush load should not exceed allowable limit. The geometric dimensions of tubes including diameter, length and thickness are chosen as design variables. The Non-domi...

With the huge global and wide range of attention placed upon quality, promoting and optimize the reliability of the products during the design process has turned out to be a high priority. In this study, the researcher have adopted one of the existing models in the reliability science and propose a bi-objective model for redundancy allocation in the series-parallel systems in accordance with th...

In design and fabricate drive shafts with high value of fundamental natural frequency that represented high value of critical speed; using composite materials instead of typical metallic materials could provide longer length shafts with lighter weight. In this paper, multi-objective optimization (MOP) of a composite drive shaft is performed considering three conflicting objectives: fundamental ...

In this study a class of Multi-Objective Genetic Algorithms (MOGAs) is proposed to select the most relevant features for the problem of speech-based emotion recognition. The employed evolutionary algorithms are the Strength Pareto Evolutionary Algorithm (or SPEA), the Preference-Inspired CoEvolutionary Algorithm with goal vectors (or PICEA), and the Nondominated Sorting Genetic Algorithm II (or...