The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach

In many seasonal industries, customer demands are constantly changing over time, and accordingly the facility layout should be re-optimized in a timely manner to adapt to changing material handling patterns among manufacturing departments. This paper investigates the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a dynamic manufacturing environment during a given planning horizon. The AFLP is decomposed into a master problem and a combination set of static facility layout problems (FLPs, the slave problems) without loss of optimality, and all problems are formulated as mixed-integer linear programming (MILP) models that can be solved by MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm with a computational complexity of O(n 2) is developed for the master problem, and an improved linear programming based problem evolution algorithm (PEA-LP) is developed for the traditional static FLP. Computational experiments are conducted on two new problems and twelve well-known benchmark problems from the literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with practical sizes of problem instances. In addition, the improved PEA-LP found new best solutions for five benchmark problems

The continuous pollution routing problem

In this paper, we presented an ε-accurate approach to conduct a continuous optimization on the pollution routing problem (PRP). First, we developed an ε-accurate inner polyhedral approximation method for the nonlinear relation between the travel time and travel speed. The approximation error was controlled within the limit of a given parameter ε, which could be as low as 0.01% in our experiments. Second, we developed two ε-accurate methods for the nonlinear fuel consumption rate (FCR) function of a fossil fuel-powered vehicle while ensuring the approximation error to be within the same parameter ε. Based on these linearization methods, we proposed an ε-accurate mathematical linear programming model for the continuous PRP (ε-CPRP for short), in which decision variables such as driving speeds, travel times, arrival/departure/waiting times, vehicle loads, and FCRs were all optimized concurrently on their continuous domains. A theoretical analysis is provided to confirm that the solutions of ε-CPRP are feasible and controlled within the predefined limit. The proposed ε-CPRP model is rigorously tested on well-known benchmark PRP instances in the literature, and has solved PRP instances optimally with up to 25 customers within reasonable CPU times. New optimal solutions of many PRP instances were reported for the first time in the experiments

Brownfield Factory Layout Planning using Realistic Virtual Models

To stay competitive in an increasingly digitalised and global context, manufacturing companies need to increase productivity and decrease waste. This means their production systems must improve; something they can achieve in a multitude of ways. For example, increasing the level of automation, improving scheduling and improving product and process flows. Often, these production system improvements entail redesigning the system to incorporate these ensuing changes; a unique and temporary endeavour that is often structured as a project. One part of the production system design process is layout planning, in which the positions of operators, workstations, machines and other parts of the system are decided. This planning process can have a major impact on the overall efficiency of operations.In industrial settings, factory layout planning is often conducted in brownfield settings. In other words, in operational facilities. Since every production system and facility is unique, so is every factory layout planning project. Each such project has different preconditions, existing knowledge, availability and quality of data, lead-times, expectations and driving forces, to name just a few. If factory layout planning were treated as a design problem (more subjective than mathematical in nature), it would be hard to produce a mathematical solution for an optimal layout that would also work in reality. Instead, if a layout is developed and adapted to all real constraints and factors while it is being developed, the result would more likely be installable and work as expected.The long-term vision of this thesis is of a future in which sustainable manufacturing industry continues playing a vital role in society, because its contribution is more than just economic. A future in which the manufacturing industry is appreciated and engaged with by the local community; in which high performance is connected to the successful adoption and efficient use of digital tools in developing and improving existing brownfield production systems. This thesis aims to ensure that manufacturing industry adopts realistic virtual models in its brownfield factory layout planning processes. It does this by identifying and describing common challenges and how they may be reduced by developing and using realistic virtual models. This leads to improvements in the planning, installation and operational phases of production systems.The findings of this thesis show that brownfield factory layout planning represents a significant proportion of industrial layout planning. Its challenges lie mainly in the areas of data accuracy and richness. There are difficulties in grasping scale and perspective, communicating ideas and gathering input in the layout planning phase. By applying 3D laser scanning to provide accurate data and virtual reality to provide immersion and scale, realistic virtual models have been created. These reduce or eliminate the challenges stated above and allow more employees to be involved in the layout planning process. This, in turn, results in the identification of flaws in the layout and improvements in the early stages, rather than during or after installation. There is also an overall improvement to brownfield factory change processes, with costs that pale by comparison to the total cost of layout changes

Overview of Dynamic Facility Layout Planning as a Sustainability Strategy

[EN] The facility layout design problem is significantly relevant within the business operations strategies framework and has emerged as an alternate strategy towards supply chain sustainability. However, its wide coverage in the scientific literature has focused mainly on the static planning approach and disregarded the dynamic approach, which is very useful in real-world applications. In this context, the present article offers a literature review of the dynamic facility layout problem (DFLP). First, a taxonomy of the reviewed papers is proposed based on the problem formulation current trends (related to the problem type, planning phase, planning approach, number of facilities, number of floors, number of departments, space consideration, department shape, department dimensions, department area, and materials handling configuration); the mathematical modeling approach (regarding the type of model, type of objective function, type of constraints, nature of market demand, type of data, and distance metric), and the considered solution approach. Then, the extent to which recent research into DFLP has contributed to supply chain sustainability by addressing its three performance dimensions (economic, environmental, social) is described. Finally, some future research guidelines are provided.This research was funded by the Spanish Ministry of Science, Innovation and Universities Project CADS4.0, grant number RTI2018-101344-B-I00; and the Valencian Community ERDF Programme 2014-2020, grant number IDIFEDER/2018/025.Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2020). Overview of Dynamic Facility Layout Planning as a Sustainability Strategy. Sustainability. 12(19):1-16. https://doi.org/10.3390/su12198277S1161219Ghassemi Tari, F., & Neghabi, H. (2015). A new linear adjacency approach for facility layout problem with unequal area departments. Journal of Manufacturing Systems, 37, 93-103. doi:10.1016/j.jmsy.2015.09.003Kheirkhah, A., Navidi, H., & Messi Bidgoli, M. (2015). Dynamic Facility Layout Problem: A New Bilevel Formulation and Some Metaheuristic Solution Methods. IEEE Transactions on Engineering Management, 62(3), 396-410. doi:10.1109/tem.2015.2437195Altuntas, S., & Selim, H. (2012). 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