Mathematical programming models for supply chain production and transport planning

By Josefa Mula, David Peidro, Manuel Díaz-Madroñero, Eduardo Vicens. European Journal of Operational Research, 2010

440 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/ad5183f7e2405a9539c86dd593f5bb064f2695d5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Josefa Mula
2. David Peidro
3. R. Poler

In Management Information Systems

1. Jacqueline Bloemhof-Ruwaard
2. Jack G. A. J. van der Vorst
3. Mehmet Soysal
4. R. Poler
5. Josefa Mula
6. Poorya Farahani
7. Martin Grunow
8. Renzo Akkerman

In Management Science and Operations Research

1. R. Poler
2. Josefa Mula

Citations in the corpus

• The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand (2010, background): “In this context, with the objective of obtaining optimal solutions related to the minimization of costs, several authors have studied the modelling of supply chain planning processes through mathematical programming models (see, for instance, Alemany et al. (2009) and Mula et al. (2010)).”
• Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges (2010, methodology): “In terms of objectives, there is in the literature again a large focus on financial aspects, occasionally combined with customer-related aspects such as service levels or flexibility (Mula et al., 2010).”
• A Review on Quantitative Models for Sustainable Food Logistics Management (2012, background): “Nevertheless, the changing system still leads to the need of advanced models and tools for planning SC operations (Mula et al., 2010).”