A fuzzy model for shortage planning under uncertainty due to lack of homogeneity in planned production lots

Alemany, M. M. E.; Grillo, Hanzel; Ortíz, Ángel; Fuertes-Miquel, Vicente S.

doi:10.1016/j.apm.2014.12.057

Cited by 18 publications

(8 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Responsiveness, robustness, and resilience (known as "Triple R") become more and more important in logistics and material handling [72] because customer satisfaction is based on "Triple R"-based performance of manufacturing and related logistics operations [73]. The objective functions and constraints are based on the problems of typical material handling related problems, like facility location [74], allocation [75], lot sizing [76][77][78], shortage planning [79], scheduling [80], inventory planning [81], and ergonomic [82] and trade policy aspects [83]. Integrated approaches [52], multi-objective optimization problems [53] can be solved with other effective optimization methods, like teaching-learning based optimization [54], force generated graph algorithms [55], agent-based optimization methods [56], or TOPSIS [57].…”

Section: Content Analysismentioning

confidence: 99%

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

et al. 2019

View full text Add to dashboard Cite

In the context of Industry 4.0, the matrix production concept represents revolutionary solutions from a technological and logistics point of view. In a matrix production system, flexible, configurable production and assembly cells are arranged in a grid layout, and the in-plant supply is based on autonomous vehicles. Adaptable and flexible material handling solutions are required to perform the dynamically changing supply-demands of standardized and categorized manufacturing and assembly cells. Within the frame of this paper, the authors describe the in-plant supply process of matrix production and the optimization potential in these processes. After a systematic literature review, this paper introduces the structure of matrix production as a cyber-physical system focusing on logistics aspects. A mathematical model of this in-plant supply process is described including extended and real-time optimization from routing, assignment, and scheduling points of view. The optimization problem described in the model is an NP-hard problem. There are no known efficient analytical methods to find the best solution for this kind of problem; therefore, we use heuristics to find a suitable solution for the above-described problem. Next, a sequential black hole–floral pollination heuristic algorithm is described. The scenario analysis, which focuses on the clustering and routing aspects of supply demands in a matrix production system, validates the model and evaluates its performance to increase cost-efficiency and warrants environmental awareness of the in-plant supply in matrix production.

show abstract

Section: Content Analysismentioning

confidence: 99%

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

et al. 2019

View full text Add to dashboard Cite

show abstract

“…There are also other works that study the problem of the LHP, and even in the ceramic sector [31] or [32]. In [33] a review of the works that propose mathematical models to support the order promising process in LHP situations is made.…”

Section: Literature Reviewmentioning

confidence: 99%

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

2019

View full text Add to dashboard Cite

Lack of homogeneity in the product (LHP) is a problem when customers require homogeneous units of a single product. In such cases, the optimal allocation of inventory to orders becomes much more complex. Furthermore, in an MTS environment, an optimal initial allocation may become less than ideal over time, due to different circumstances. This problem occurs in the ceramics sector, where the final product varies in tone and calibre. This paper proposes a methodology for the reallocation of inventory to orders in LHP situation (MERIO-LHP) and a model-based decision-support system (DSS) to support the methodology, which enables an optimal reallocation of inventory to order lines to be carried out in real businesses environments in which LHP is inherent. The proposed methodology and model-based DSS were validated by applying it to a real case at a ceramics company. The analysis of the results indicates that considerable improvements can be obtained with regard to the quantity of orders fulfilled and sales turnover.

show abstract

“…There are numerous applications of OR to different supply chain management processes such as the supply chain design, operation planning (Grillo et al, 2016a;Mundi et al, 2016;Hegeman et al, 2014;Mundi et al, 2013;Alemany et al, 2011;Alemany et al, 2010) and order management (Grillo et al, 2016b;Alemany et al, 2015;Boza et al, 2014;Alemany et al, 2013). Lowe and Preckel (2004) claim that effective practices for other supply chains cannot be directly extrapolated to AFSC due to its own characteristics.…”

Section: Related Workmentioning

confidence: 99%

Métodos y Modelos Deterministas e Inciertos para la Gestión de Cadenas de Suministro Agroalimentarias

Esteso

Alemany

Ortíz

2017

DyO

Self Cite

View full text Add to dashboard Cite

El mercado de productos agrícolas está en continuo crecimiento, al igual que la preocupación social en temas alimentarios como la calidad y seguridad alimentaria. Esto genera la necesidad de desarrollar modelos y herramientas para gestionar las cadenas de suministro agroalimentarias de manera ajustada y teniendo en cuenta sus características y fuentes de incertidumbre inherentes. Este articulo presenta el estado actual de un proyecto cuyos principales objetivos son: describir la complejidad enfrentada por los decisores de las cadenas de suministro agroalimentarias, y desarrollar nuevas herramientas basadas en programación matemática para apoyar la toma de decisiones en este sector.

show abstract

A fuzzy model for shortage planning under uncertainty due to lack of homogeneity in planned production lots

Cited by 18 publications

References 45 publications

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

Métodos y Modelos Deterministas e Inciertos para la Gestión de Cadenas de Suministro Agroalimentarias

Contact Info

Product

Resources

About