In a typical discrete manufacturing process, new type of reconfigurable production line is introduced, which aims to help small- and mid-size enterprises improve machine utilization reduce cost. order effectively handle the scheduling problem for system, an improved multi-objective particle swarm optimization algorithm based on Brownian motion (MOPSO-BM) proposed. Since existing MOPSO algorithm...

This paper proposes a novel multi-objective ant colony system (MOACS) approach to solve the cooperative task allocation problem of multi-robot systems. The is formulated as multiple traveling salesman (MTSP). objectives are minimize total and maximum cost robotic vehicles so that workload each vehicle could be balanced. time matrices salesmen different asymmetric due flight speeds executing tas...

The accurate classification of reservoir recovery factor is dampened by irregularities such as noisy and high-dimensional features associated with the measurements or characterization. These irregularities, especially a larger number features, make it difficult to perform factor, generated are usually heterogeneous. Consequently, imperative select relevant while preserving amplifying accuracy. ...

<span>Worldwide, the COVID-19 widespread has significant impact on a great number of people. The hospital admittance issue for patients with been optimized by previous research. Identifying symptoms that can be used to determine patient's health status, whether they are dead or alive it is difficult task medical professionals. To solve this issue, multi-objective group counselling optimiz...

<p style='text-indent:20px;'>The shortage of relief vehicles capacity is a common issue throughout disastrous situations due to the abundance injured people who need urgent medical aid. Hence, ambulances fleet management highly important save as many individuals possible. In this regard, present paper defines different patient groups based on their needs and characteristics. order provide...

Due to limited financial resources and high costs of infrastructure projects, project stakeholders seek gain maximum profits with optimal resource utilization as well cost time minimization. Therefore, this study presents a multi-mode resource-constrained scheduling model considering the uncertain parameters together goals maximizing net present value minimizing usage fluctuation. Also, assumpt...

Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...

This study presents a multi-objective optimization approach for designing hybrid renewable energy systems electric vehicle (EV) charging stations that considers both economic and reliability factors as well seasonal variations in production consumption. Four algorithms, MOPSO, NSGA-II, NSGA-III, MOEA/D, were evaluated terms of their convergence, diversity, efficiency, robustness. Unlike previou...

Abstract The integration of Internet Things devices onto the Blockchain implies an increase in transactions that occur on Blockchain, thus increasing storage requirements. A solution approach is to leverage cloud resources for storing blocks within chain. paper, therefore, proposes two solutions this problem. first being improved hybrid architecture design which uses containerization create a s...