evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

• A hybrid machine learning strategy is developed for complex chemical processes. Continuum lumping kinetic embedded into the neural network framework. NSGA-II used multi-objective optimisation of hydrocracking process. Catalytic processes such as hydrocracking, gasification and pyrolysis play a vital role in renewable energy net zero transition. Due to non-linear behaviours during operation, c...

During last decades, developing multi-objective evolutionary algorithms for optimization problems has found considerable attention. Flexible job shop scheduling problem, as an important scheduling optimization problem, has found this attention too. However, most of the multi-objective algorithms that are developed for this problem use nonprofessional approaches. In another words, most of them c...

This paper proposes an approach which is based on a multi objective genetic algorithm to resolve the vehicles routing problem with time windows (VRPTW). The context of this problem is to plan a set of routes to serve heterogeneous demands respecting several constraints (only one depot, vehicles limited capacity, windows of time). We used an approach based on a multi-objective optimization to re...

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...

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...

The primary function of a suspension system of a vehicle is to isolate the road excitations experienced by the tires from being transmitted to the passengers. In this paper, we formulate an optimal vehicle suspension design problem with the quarter-car vehicle dynamic model. A new multi-objective genetic algorithm is used for Pareto optimization of a two-degree of freedom vehicle vibration mode...