Integrating facility layout design and aisle structure in manufacturing systems: Formulation and exact solution

A conceptual framework for multi-objective facility layout planning by a bottom-up approach

“…In manufacturing systems, aisles are paths that allow the movement of personnel and the transport of materials between different work areas. The aisle structure contributes to plant layout efficiency due to its impact on reducing the distance travelled by the materials flow, the average flow time and MHCs (Pourvaziri et al, 2021). Therefore, to achieve an adequate plant layout, it is not enough to determine the position of the departments, machines and workstations in the physical space, but it is also essential to integrate the aisle structure design (Friedrich et al, 2018).…”

“…Therefore, to achieve an adequate plant layout, it is not enough to determine the position of the departments, machines and workstations in the physical space, but it is also essential to integrate the aisle structure design (Friedrich et al, 2018). Excluding works addressing the double-row layout problem, only a few articles in the literature considered the aisle structure design in an integrated manner when designing the plant layout of manufacturing systems while considering single-objective mathematical models (Chang et al, 2006;Gómez et al, 2003;Lasch, 2016, 2019;Lee et al, 2005;Pourvaziri et al, 2021), and only three did so in the specific mFLP context (Leno et al, 2012;Navidi et al, 2012).…”

Optimal Design of a Ship Multitasking Cabin Layout Based on the Interval Optimization Method

“…Drira [9] summarized the research conducted by scholars and pointed out several research directions. Pourvaziri [10] proposed a new model of linear programming in FLP to optimize the width and number of passages and verify the effectiveness of the method through calculations. Shamsodin [11] proposed a new mathematical model for the Dynamic Facility Layout Problem, and solved the model by combining an improved genetic algorithm and a cloud model-based simulated annealing algorithm.…”

“…The minimum area of the cabin arranged in each row is required to be no more than the usable area of the row. { 𝛼(𝑥 1 ) + 𝛼(𝑥 2 ) + 𝛼(𝑥 3 ) ≤ 𝑆 1 𝛼(𝑥 4 ) + 𝛼(𝑥 5 ) + 𝛼(𝑥 6 ) + 𝛼(𝑥 7 ) ≤ 𝑆 2 ⋯ 𝛼(𝑥 𝑛−2 ) + 𝛼(𝑥 𝑛−1 ) + 𝛼(𝑥 𝑛 ) ≤ 𝑆 𝑚 (10) where: 𝑚 represents the maximum number of rows divided by the longitudinal channel, and 𝛼(𝑥 𝑗 ) represents the minimum areas' reference of the cabin corresponding to the location.…”

“…Fig 15. Comparison of distance between C2# and C3# where: selecting the cabin groups(9)(10)(11)(12)(13)(14)(15), (72-73) for comparison. The red dotted line represents the shortest path between cabin groups (9-15), the blue dotted line represents the shortest path between cabin groups (72-73).From the comparison of (a) and (b) in Fig.15, it can be seen that the distance between the two sets of cabins under the two methods is relatively small, which can better meet the needs of proximity between the cabins.…”