Integrated quadratic assignment and continuous facility layout problem

In this paper, an integrated layout model has been considered to incorporate intra and inter-department layout. In the proposed model, the arrangement of facilities within the departments is obtained through the QAP and from the other side the continuous layout problem is implemented to find the position and orientation of rectangular shape departments on the planar area. First, a modified version of QAP with fewer binary variables is presented. Afterward the integrated model is formulated based on the developed QAP. In order to evaluate material handling cost precisely, the actual position of machines within the departments (instead of center of departments) is considered. Moreover, other design factors such as aisle distance, single or multi row intra-department layout and orientation of departments have been considered. The mathematical model is formulated as mixed-integer programming (MIP) to minimize total material handling cost. Also due to the complexity of integrated model a heuristic method has been developed to solve large scale problems in a reasonable computational time. Finally, several illustrative numerical examples are selected from the literature to test the model and evaluate the heuristic

A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

In this paper, a new mathematical model in cellular manufacturing systems (CMSs) has been presented. In order to increase the performance of manufacturing system, the production quantity of parts has been considered as a decision variable, i.e. each part can be produced and outsourced, simultaneously. This extension would be minimized the unused capacity of machines. The exceptional elements (EEs) are taken into account and would be totally outsourced to the external supplier in order to remove intercellular material handling cost. The problem has been formulated as a mixed-integer programming to minimize the sum of manufacturing variable costs under budget, machines capacity and demand constraints. Also, to evaluate advantages of the model, several illustrative numerical examples have been provided to compare the performance of the proposed model with the available classical approaches in the literature

A dynamic programming–enhanced simulated annealing algorithm for solving bi-objective cell formation problem with duplicate machines

Cell formation process is one of the first and the most important steps in designing cellular manufacturing systems. It consists of identifying part families according to the similarities in the design, shape, and presses of parts and dedicating machines to each part family based on the operations required by the parts. In this study, a hybrid method based on a combination of simulated annealing algorithm and dynamic programming was developed to solve a bi-objective cell formation problem with duplicate machines. In the proposed hybrid method, each solution was represented as a permutation of parts, which is created by simulated annealing algorithm, and dynamic programming was used to partition this permutation into part families and determine the number of machines in each cell such that the total dissimilarity between the parts and the total machine investment cost are minimized. The performance of the algorithm was evaluated by performing numerical experiments in different sizes. Our computational experiments indicated that the results were very encouraging in terms of computational time and solution quality

Solving an Integrated Cell Formation, Group Layout and Routing Problem Using Dynamic Programming Based Metaheuristic Algorithms

The cell formation problem and the group layout problem, both are two important problems in designing a cellular manufacturing system. The cell formation problem is consist of grouping parts into part families and machines into production cells. In addition, the group layout problem is to find the arrangement of machines within the cells as well as the layout of cells. In this paper, an integrated approach is presented to solve the cell formation, group layout and routing problems. By Considering the dimension of machines, the width of the aisles, and the maximum permissible length of the plant site, a new framework, called spiral layout, is suggested for the layout of cellular manufacturing systems. To extend the applicability of the problem, parameters such as part demands, operation sequences, processing times and machine capacities are considered in the problem formulation. The problem is formulated as a bi-objective integer programming model, in which the first objective is to minimize the total material handling cost and the second one is to maximize the total similarity between machines. As the problem is NP-hard, three metaheuristic algorithms, based on Genetic Algorithm and Simulated Annealing are proposed to solve it. To enhance the performance of the algorithms, a Dynamic Programming algorithm is embedded within them. The performance of the algorithms is evaluated by solving numerical examples from the related literature. Finally, a comparison is carried out between the proposed spiral layout and the linear multi-row layout which has recently presented in the literatur

A multi-period sustainable hydrogen supply chain model considering pipeline routing and carbon emissions : The case study of Oman

This paper presents a mathematical model for a multi-period hydrogen supply chain design problem consider-ing several design features not addressed in other studies. The model is formulated as a mixed-integer program allowing the production and storage facilities to be extended over time. Pipeline and tube trailer transport modes are considered for carrying hydrogen. The model also allows finding the optimal pipeline routes and the number of transport units. The objective is to obtain an efficient supply chain design within a given time frame in a way that the demand and carbon dioxide emissions constraints are satisfied and the total cost is minimized. A computer program is developed to ease the problem-solving process. The computer program extracts the geographical information from Google Maps and solves the problem using an optimization solver. Finally, the applicability of the proposed model is demonstrated in a case study from Oman

Maximizing value yield in wood industry through flexible sawing and product grading based on wane and log shape

The optimization of sawing processes in the wood industry is critical for maximizing efficiency and profitability. The introduction of computerized tomography scanners provides sawmill operators with three-dimensional internal models of logs, which can be used to assess value and yield more accurately. We present a methodology for solving the sawing optimization problem employing a flexible sawing scheme that allows greater flexibility in cutting logs into products while considering product quality classes influenced by wane defects. The methodology has two phases: preprocessing and optimization. In the preprocessing phase, two alternative algorithms are given that generate and evaluate the potential sawing positions of products by considering the 3D surface of the log, product size requirements, and product quality classes. In the optimization phase, a maximum set-packing problem is solved for the preprocessed data using mixed-integer programming (MIP), aiming to obtain a feasible cut pattern that maximizes value yield. This is implemented in a system named FlexSaw, which takes advantage of parallel computation during the preprocessing phase and utilizes a MIP solver during the optimization phase. The proposed sawing methods are evaluated on the Swedish Pine Stem Bank. Additionally, FlexSaw is compared with an existing tool that utilizes cant sawing. Results demonstrate the superiority of flexible sawing. While the practical feasibility of implementing a flexible way of sawing logs is constrained by the limitations of current sawmill machinery, the potential increase in yield promotes the exploration of alternative machinery in the wood industry.This work was supported by Sweden’s Innovation Agency (VINNOVA) via BioInnovation under grant 2020–03734.</p

GaAs1−yBiy Raman signatures: illuminating relationships between the electrical and optical properties of GaAs1−yBiy and Bi incorporation

We report the use of two Raman signatures, the Bi-induced longitudinal-optical-plasmon-coupled (LOPC) mode and the GaAs Fröhlich scattering intensity, present in nominally undoped (100) GaAs1−yBiy to predict the 300K photoluminescence intensity and Bi composition (y) in GaAs1−yBiy. The LOPC mode is used to calculate the hole concentration in GaAs1−yBiy epitaxial layers. A linear relationship between hole concentration and photoluminescence intensity is found for a range of samples grown at various temperatures and growth rates. In addition, the composition (y) of Bi in GaAs1−yBiy is also found to be linearly related to the GaAs Fröhlich scattering intensity