Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

Abstract

Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

“…To achieve robust, resilient and sustainable agri-food supply chains is very complex because they face more sources of uncertainty and risks in comparison with other supply chains that give rise to serious questions and concerns about their economic, environmental and social performance. Several studies identify agricultural sources of uncertainty [117,118,119] and how to model them [120]. In [119] four types of crop-based uncertainty are identified: Product (shelf-life, deterioration rate, lack of homogeneity, food quality and food safety), Process (harvesting yield, supply lead time, resource needs, production), Market (demand, market prices) and Environment (weather, pests & diseases and regulations).…”

Research trends in combinatorial optimization

“…Table A4). The consideration of uncertainties also becomes increasingly relevant for the real‐world application areas discussed above like production planning (e.g., inhomogeneity of products, Mundi et al., 2019) or energy system analysis (e.g., stochastic nature of renewables and unknown future global energy and economy outlook, Mavromatidis et al., 2018).…”

Un análisis de revisiones de modelos y algoritmos para la optimización de planes de aprovisionamiento, producción y distribución de la cadena de suministro

“…Con respecto a lo mencionado, dos revisiones estudian la cadena de suministro desde la perspectiva de incertidumbre (Peidro et al 2009;Mundi et al 2019). Entre ambos estudios hay 10 años de diferencia, no obstante, los dos coinciden que trabajos futuros deben desarrollar modelos de programación difusa para manejar datos imprecisos y/o no disponibles.…”

“…Entre ambos estudios hay 10 años de diferencia, no obstante, los dos coinciden que trabajos futuros deben desarrollar modelos de programación difusa para manejar datos imprecisos y/o no disponibles. Es importante señalar que Mundi et al (2019) utilizaron el trabajo de (Peidro et al 2009) como base para su investigación, añadiendo la característica de falta de homogeneidad en los productos. Además, Peidro et al (2009), sugieren otras líneas de investigación como el desarrollo de nuevos modelos híbridos mediante la combinación de modelos basados tanto en la teoría de conjuntos difusos como en la simulación, que puedan considerar enfoques de control predicti-vo.…”

“…Los autores hacen hincapié en la utilización de modelos basados en inteligencia artificial, y en el análisis de los mecanismos de gestión de la incertidumbre desde una perspectiva cuantitativa. Por otra parte, Mundi et al (2019) sugieren el desarrollo de modelos de optimización y técnicas de solución para abordar la incertidumbre en la demanda de productos con falta de homogeneidad.…”