Soft Computing Methodology to Optimize the Integrated Dynamic Models of Cellular Manufacturing Systems in a Robust Environment

Abstract

Machine learning, neural networks, and metaheuristic algorithms are relatively new subjects, closely related to each other: learning is somehow an intrinsic part of all of them. On the other hand, cell formation (CF) and facility layout design are the two fundamental steps in the CMS implementation. To get a successful CMS design, addressing the interrelated decisions simultaneously is important. In this article, a new nonlinear mixed-integer programming model is presented which comprehensively considers solving the integrated dynamic cell formation and inter/intracell layouts in continuous space. In the proposed model, cells are configured in flexible shapes during the planning horizon considering cell capacity in each period. This study considers the exact information about facility layout design and material handling cost. The proposed model is an NP-hard mixed-integer nonlinear programming model. To optimize the proposed problem, first, three metaheuristic algorithms, that is, Genetic Algorithm (GA), Keshtel Algorithm (KA), and Red Deer Algorithm (RDA), are employed. Then, to further improve the quality of the solutions, using machine learning approaches and combining the results of the aforementioned algorithms, a new metaheuristic algorithm is proposed. Numerical examples, sensitivity analyses, and comparisons of the performances of the algorithms are conducted.

An Economic and Environmental Optimization Model in a Micro Grid with Demand Response

“…The Fuzzy satisfying method is used to opt the best trade-off solution out of the provided Pareto solutions. In this approach, a fuzzy membership is devoted to each Pareto front solution some value between 0 and 1 which is calculated by ( 14) [41]- [43].…”

A New Mathematical Model for Cell Layout Problem considering Rotation of Unequal Dimensions of Cells and Machines

“…Salimpour et al [40] developed CF, intracellular and intercellular layout problems, and machines of unequal dimensions. Golmohammadi et al [41] considered the problem of facility layout by integrating CF in continuous space and intercellular and intracellular layouts. Mondal et al [42] hypothesized the problems of intercellular layout and CF in CMS and ofered a model for minimizing cell load variation and reducing intercellular movements.…”

Optimal Energy-Saving in Smart Energy Hub Considering Demand Management

“…The maximization of the energy hub profit using technical and economic operation is proposed in [37], in mentioned reference strategic conversion of demand is implemented in energy hub system. In [38], the security-constrained modelling is proposed in energy hub by unit commitment strategy and value-at-risk (CVaR) management. In [39], weighted sum method is implemented to minimizing costs and emission in energy hub by direct control strategy of demand at peak times.…”