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[EN] Fruit Supply Chains (SCs) are influenced by uncontrollable natural factors causing heterogeneity in their products, as regards certain attributes that are relevant to customers and vary over time because of the shelf-life. As a consequence customers should be served not only with the required quantity and due date as usual, but also with the quality, freshness and homogeneity specified in their orders. The order promising process (OPP) is based on the uncommitted availability of homogeneous product quantities in planned lots (ATP) that are uncertain. Therefore, there is a risk of not being reliable in the commitments because of discrepancies between the real and planned homogeneous quantities. Furthermore, due to the shelf-life (SL), serving customers with the freshest product introduce the risk of increasing waste because of the aging process. To efficiently manage these risks, this work proposes a mathematical model for handling the heterogeneous ATP in fruit SCs and a pricing policy based on the product SL in the moment of delivery. In order to illustrate the application of the modelling approach, a short numerical example is introduced. The example evidences a conflictive situation when optimizing the assignation of homogeneous ATP between serving orders with fresh and more valuable product, what could lead to increase the risk of having waste because of expiration, and consequently, more costs and less profit. ; This research has been supported by the Ministry of Science, Technology and Telecommunications, government of Costa Rica (MICITT), through the program of innovation and human capital for competitiveness (PINN) (PED-019-2015-1). ; Grillo-Espinoza, H.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2016). Modelling Pricing Policy Based on Shelf-Life of Non Homogeneous Available-To-Promise in Fruit Supply Chains. IFIP Advances in Information and Communication Technology. 480:608-617. https://doi.org/10.1007/978-3-319-45390-3_52 ; S ; 608 ; 617 ; 480 ; Alarcon, F., Alemany, M.M.E., Lario, F.C., Oltra, R.F.: ...

[EN] Ensuring gender equality in organizations is an increasingly necessary and demanded aspect of legislation; implies satisfying the constitutional right of equality. Until now, in his study, has not taken into account variants that can affect the agility and resilience of the organization. The present article proposes the preliminary definition of a maturity model that allows to evaluate the incorporation of the gender perspective without limiting the agility and resilience in the organization, extracting the relation that indicates which aspects of agility and resilience can be affected by the areas where the gender perspective should be incorporated. It is proposed in this article to extend the alignment beyond information systems and technologies, incorporating aspects such as agility, resilience and gender perspective in supply chains. In this sense, the alignment will refer to the degree to which incorporating the gender perspective into the design of supply chains favors and drives agility and resilience, and how agile and resilient chains facilitate the incorporation of perspectives of gender in the design of the chain. On one hand, key areas have been identified as follows: Government and values, Work environment, Supply chain, Community, Consumers and Investment, and the general levels of maturity to be achieved. On the other hand, it has been defined the aspects to be taken into account to ensure their agility and resilience and the relationships with the key areas. The key area of government and values involves establishing the principles guiding considerations on gender equality in policies that determine organizational culture. These principles should be extended to all areas included as important to ensure the agility and resilience of the organization. Work environment corresponds to the definition of equal opportunities for women and men, eliminating obstacles that limit their participation. What will be related to the definition of facilities and resources, processes, people and strategy, ...

57 64 63 ; S ; [EN] Ensuring gender equality in organizations is an increasingly necessary and demanded aspect of legislation; implies satisfying the constitutional right of equality. Until now, in his study, has not taken into account variants that can affect the agility and resilience of the organization. The present article proposes the preliminary definition of a maturity model that allows to evaluate the incorporation of the gender perspective without limiting the agility and resilience in the organization, extracting the relation that indicates which aspects of agility and resilience can be affected by the areas where the gender perspective should be incorporated. It is proposed in this article to extend the alignment beyond information systems and technologies, incorporating aspects such as agility, resilience and gender perspective in supply chains. In this sense, the alignment will refer to the degree to which incorporating the gender perspective into the design of supply chains favors and drives agility and resilience, and how agile and resilient chains facilitate the incorporation of perspectives of gender in the design of the chain. On one hand, key areas have been identified as follows: Government and values, Work environment, Supply chain, Community, Consumers and Investment, and the general levels of maturity to be achieved. On the other hand, it has been defined the aspects to be taken into account to ensure their agility and resilience and the relationships with the key areas. The key area of government and values involves establishing the principles guiding considerations on gender equality in policies that determine organizational culture. These principles should be extended to all areas included as important to ensure the agility and resilience of the organization. Work environment corresponds to the definition of equal opportunities for women and men, eliminating obstacles that limit their participation. What will be related to the definition of facilities and resources, processes, people ...

[EN] Mathematical programming models are invaluable tools at decision making, assisting managers to uncover otherwise unattainable means to optimize their processes. However, the value they provide is only as good as their capacity to capture the process domain. This information can only be obtained from stakeholders, i.e., clients or users, who can hardly communicate the requirements clearly and completely. Besides, existing conceptual models of mathematical programming models are not standardized, nor is the process of deriving the mathematical programming model from the concept model, which remains ad hoc. In this paper, we propose an agile methodology to construct mathematical programming models based on two techniques from requirements engineering that have been proven effective at requirements elicitation: the language extended lexicon (LEL) and scenarios. Using the pair of LEL + scenarios allows to create a conceptual model that is clear and complete enough to derive a mathematical programming model that effectively captures the business domain. We also define an ontology to describe the pair LEL + scenarios, which has been implemented with a semantic mediawiki and allows the collaborative construction of the conceptual model and the semi-automatic derivation of mathematical programming model elements. The process is applied and validated in a known fresh tomato packing optimization problem. This proposal can be of high relevance for the development and implementation of mathematical programming models for optimizing agriculture and supply chain management related processes in order to fill the current gap between mathematical programming models in the theory and the practice. ; This work was supported by the European Commission, project RUC-APS, grant number 691249, funded by the European Union's research and innovation programme under the H2020 Marie SklodowskaCurie Actions; and the Argentinian National Agency for Scientific and Technical Promotion (ANPCyT), grant number PICT-2015-3000. ; Garrido, A.; ...

[EN] 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. ; This research was initiated within the framework of the project funded by the Ministerio de Economía y Competitividad [Ref. DPI2011-23597] entitled 'Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity' (PLANGES-FHP) already finished. After, the project leading to this application has received funding from the European Union's research and innovation programme under the H2020 Marie Skłodowska-Curie Actions with the grant agreement No 691249, Project entitled 'Enhancing and implementing Knowledge based ICT solutions within high Riskand Uncertain Conditions for Agriculture Production Systems' (RUC-APS). ; Mundi, I.; Alemany Díaz, MDM.; Poler, R.; Fuertes-Miquel, VS. (2019). Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model. International Journal of Production Research. 57(15-16):5239-5283. https://doi.org/10.1080/00207543.2019.1566665 ; S ...

Traditionally, supply chain planning problems consider variables with uncertainty associated with uncontrolled factors. These factors have been normally modelled by complex methodologies where the seeking solution process often presents high scale of difficulty. This work presents the fuzzy set theory as a tool to model uncertainty in supply chain planning problems and proposes the particle swarm optimisation (PSO) metaheuristics technique combined with a backward calculation as a solution method. The aim of this combination is to present a simple effective method to model uncertainty, while good quality solutions are obtained with metaheuristics due to its capacity to find them with satisfactory computational performance in complex problems, in a relatively short time period. ; This research is partly supported by the Spanish Ministry of Economy and Competitiveness projects 'Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity' (PLANGES-FHP) (Ref. DPI2011-23597) and 'Operations design and Management of Global Supply Chains' (GLOBOP) (Ref. DPI2012-38061-C02-01); by the project funded by the Polytechnic University of Valencia entitled 'Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics' (PAID-06-12); and by the Ministry of Science, Technology and Telecommunications, government of Costa Rica (MICITT), through the incentive program of the National Council for Scientific and Technological Research (CONICIT) (contract No FI-132-2011). ; Grillo Espinoza, H.; Peidro Payá, D.; Alemany Díaz, MDM.; Mula, J. (2015). Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model. International Journal of Bio-Inspired Computation. 7(3):157-169. https://doi.org/10.1504/IJBIC.2015.069557 ; S ; 157 ; 169 ; 7 ; 3

[EN] Decision making for farms is a complex task. Farmers have to fix the price of their production but several parameters have to be taken into account: harvesting, seeds, ground, season etc. This task is even more difficult when a group of farmers must make the decision. Generally, optimization models support the farmers to find no dominated solutions, but the problem remains difficult if they have to agree on one solution. In order to support the farmers for this complex decision we combine two approaches. We firstly generate a set of no dominated solutions thanks to a centralized optimization model. Based on this set of solution we then used a Group Decision Support System called GRUS for choosing the best solution for the group of farmers. The combined approach allows us to determine the best solution for the group in a consensual way. This combination of approaches is very innovative for the Agriculture domain. ; The authors acknowledge the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015. One of the authors acknowledges the partial support of the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595). ; Zaraté, P.; Alemany Díaz, MDM.; Del Pino, M.; Esteso, A.; Camilleri, G. (2019). How to Support Group Decision Making in Horticulture: An Approach Based on the Combination of a Centralized Mathematical Model and a Group Decision Support System. Lecture Notes in Business Information Processing. 348:83-94. https://doi.org/10.1007/978-3-030-18819-1_7 ; S ; 83 ; 94 ; 348 ; Tweeten, L., Thompson, S.: Long-term global agricultural output supply-demand balance. Farm Policy J. 6(1), 1–16 (2009) ; Weintraub, A., Romero, C.: Operations research models and the management of agricultural and forestry resources: a review and comparison. Interfaces (Provid.) 36, 446–457 (2006). ...

This is an Accepted Manuscript of an article published in International Journal of Production Research on 2012, available online: http://www.tandfonline.com/10.1080/00207543.2011.588267. ; In this paper, we consider the master planning problem for a centralised replenishment, production and distribution ceramic tile supply chain. A fuzzy multi-objective linear programming (FMOLP) approach is presented which considers the maximisation of the fuzzy gross margin, the minimisation of the fuzzy idle time and the minimisation of the fuzzy backorder quantities. By using an interactive solution methodology to convert this FMOLP model into an auxiliary crisp single-objective linear model, a preferred compromise solution is obtained. For illustration purposes, an example based on modifications of real-world industrial problems is used. ; This research has been carried out in the framework of a project funded by the Science and Technology Ministry of the Spanish Government, entitled 'Project of reinforcement of the competitiveness of the Spanish managerial fabric through the logistics as a strategic factor in a global environment' (Ref. PSE-370000-2008-8). ; Peidro Payá, D.; Mula, J.; Alemany Díaz, MDM.; Lario Esteban, FC. (2012). Fuzzy multi-objective optimisation for master planning in a ceramic supply chain. International Journal of Production Research. 50(11):3011-3020. https://doi.org/10.1080/00207543.2011.588267 ; S ; 3011 ; 3020 ; 50 ; 11 ; Alemany, M.M.E.et al., 2010. Mathematical programming model for centralized master planning in ceramic tile supply chains.International Journal of Production Research, 48 (17), 5053–5074 ; Beamon, B. M. (1998). Supply chain design and analysis: International Journal of Production Economics, 55(3), 281-294. doi:10.1016/s0925-5273(98)00079-6 ; Chen, C.-L., & Lee, W.-C. (2004). Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices. Computers & Chemical Engineering, 28(6-7), 1131-1144. ...

[EN] Ecuador is worldwide considered as one of the main natural flower producers and exporters ¿being roses the most salient ones. Such a fact has naturally led the emergence of small and medium sized companies devoted to the production of quality roses in the Ecuadorian highlands, which intrinsically entails resource usage optimization. One of the first steps towards optimizing the use of resources is to forecast demand, since it enables a fair perspective of the future, in such a manner that the in-advance raw materials supply can be previewed against eventualities, resources usage can be properly planned, as well as the misuse can be avoided. Within this approach, the problem of forecasting the supply of roses was solved into two phases: the first phase consists of the macro-forecast of the total amount to be exported by the Ecuadorian flower sector by the year 2020, using multi-layer neural networks. In the second phase, the monthly demand for the main rose varieties offered by the study company was micro-forecasted by testing seven models. In addition, a Bayesian network model is designed, which takes into consideration macroeconomic aspects, the level of employability in Ecuador and weather-related aspects. This Bayesian network provided satisfactory results without the need for a large amount of historical data and at a low-computational cost. ; Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS ¿Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems¿ (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015. In addition, the authors are greatly grateful by the support given by the SDAS Research Group (www.sdas-group.com) ; Herrera-Granda, ID.; Lorente-Leyva, LL.; Peluffo-Ordóñez, DH.; Alemany Díaz, MDM. (2021). A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. Lecture Notes in Computer Science. ...

[EN] Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty. ; Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015 ; Alemany Díaz, MDM.; Esteso, A.; Ortiz Bas, Á.; Hernández Hormazabal, JE.; Fernández, A.; Garrido, A.; Martin, J. (2021). A conceptual framework for crop-based agri-food supply chain characterization under uncertainty. Studies in Systems, Decision and Control. 280:19-33. https://doi.org/10.1007/978-3-030-51047-3_2 ; S ; 19 ; 33 ; 280 ; Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Manage. 11, 379–384 (2006) ; Matopoulos, A., Vlachopoulou, M., Manthou, V., Manos, B.: A conceptual framework for supply chain collaboration: empirical evidence from the agri-food industry. Supply Chain Manage. ...