Abstract
The traditional machine-part cell formation problem simultaneously clusters machines and parts in different production cells from a zero–one incidence matrix that describes the existing interactions between the elements. This manuscript explores a novel alternative for the well-known machine-part cell formation problem in which the incidence matrix is composed of non-binary values. The model is presented as multiple-ratio fractional programming with binary variables in quadratic terms. A simple reformulation is also implemented in the manuscript to express the model as a mixed-integer linear programming optimization problem. The performance of the proposed model is shown through two types of empirical experiments. In the first group of experiments, the model is tested with a set of randomized matrices, and its performance is compared to the one obtained with a standard greedy algorithm. These experiments showed that the proposed model achieves higher fitness values in all matrices considered than the greedy algorithm. In the second type of experiment, the optimization model is evaluated with a real-world problem belonging to Human Resource Management. The results obtained were in line with previous findings described in the literature about the case study.
Highlights
Group technology (GT) is a manufacturing approach in which parts with a high percentage of similarities are grouped and manufactured with a small number of machines or processes [1]
In the GT literature, the group of parts with common similarities is known as part family, and the group of machines employed to process an individual part family is denoted as machine cell
It is important to stress that the comparison method implements the optimization function defined in Section 3.1 whereas the proposed model the reformulated version of the problem, Section 3.3
Summary
Group technology (GT) is a manufacturing approach in which parts with a high percentage of similarities are grouped and manufactured with a small number of machines or processes [1]. A “one” entry in that matrix indicates that this part has an operation scheduled in the corresponding machine; zero indicates that it does not In this manuscript, we explore an alternative formulation of the CF problem with non-binary values. The most commonly used methods and algorithms were Decision Tree (30%), Support Vector Machine (17%), Random Forest (17%), logistic regression (15%), K-Nearest Neighbor (11%), Multi-Layer Perceptron (4%), C4.5 algorithm (4%) and Gaussian Naïve Baye (2%) In this manuscript, we extend the set of methodologies to be implemented in the HRM area by proposing a novel method from Operations Research. Accountants assume work intensity as an intrinsic characteristic of the profession, and, due to this, they do not prioritize its improvement In this context, accountancy firms must develop job resources to lessen the stress of their employees.
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