A Collaborative Model to Improve Farmers' Skill Level by Investments in an Uncertain Context

[EN] Some small farms are forced to waste a part of their harvests for not reaching the quality standards fixed by consumers. Meanwhile, modern retailers (MR) are interested in selling more quality products to increase their profits. MR could invest in a collaboration program so the small farmers could have access to better technologies and formation to increase the proportion of quality products. Unfortunately, the demand, the quantity of harvest, the proportion of harvest being of quality, and its increase with each investment are uncertain parameters. A fuzzy model considering these uncertainties is proposed to determine the investments that MR should made to maximize the profits of the supply chain in a collaboration context. A method to transform the fuzzy model into an equivalent crisp model and an interactive resolution method are applied.The first author acknowledges the partial support of the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595). The other authors acknowledge the partial support of Project 691249, "RUCAPS: 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-MCSA-RISE-2015.Esteso, A.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Guyon, C. (2018). A Collaborative Model to Improve Farmers' Skill Level by Investments in an Uncertain Context. IFIP Advances in Information and Communication Technology. 534:590-598. https://doi.org/10.1007/978-3-319-99127-6_51S590598534Zhao, G., Liu, S., Lopez, C.: A literature review on risk sources and resilience factors in agri-food supply chains. In: Camarinha-Matos, Luis M., Afsarmanesh, H., Fornasiero, R. (eds.) PRO-VE 2017. IFIP AICT, vol. 506, pp. 739–752. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65151-4_66Esteso, A., Alemany, M.M.E., Ortiz, A.: Improving vegetables quality in small-scale farms through stakeholders collaboration. In: 12th International Conference on Industrial Engineering and Industrial Management (in Press)Sutopo, W., Hisjam, M., Yuniaristanto: An agri-food supply chain model to empower farmers for supplying deteriorated product to modern retailer. In: Yang, G.C., Ao, S.I., Huang, X., Castillo, O. (eds.) IAENG Transactions on Engineering Technologies. LNEE, vol 186, pp. 189–202. Springer, Dordrecht (2013). https://doi.org/10.1007/978-94-007-5651-9_14Sutopo, W., Hisjam, M., Yuniaristanto, Kurniawan, B.: A goal programming approach for assessing the financial risk of corporate social responsibility programs in agri-food supply chain network. In: Proceedings of the World Congress on Engineering 2013, pp. 732–736 (2013)Sutopo, W., Hisjam, M., Yuniaristanto: An agri-food supply chain model for cultivating the capabilities of farmers accessing market using social responsibility program. Int. Sch. Sci. Res. Innov. 5(11), 1588–1592 (2011)Sutopo, W., Hisjam, M., Yuniaristanto: An agri-food supply chain model to enhance the business skills of small-scale farmers using corporate social responsibility. Makara J. Technol. 16(1), 43–50 (2012)Sutopo, W., Hisjam, M., Yuniaristanto: Developing an agri-food supply chain application for determining the priority of CSR program to empower farmers as a qualified supplier of modern retailer. In: 2013 World Congress on Engineering and Computer Science, pp. 1180–1184 (2013)Wahyudin, R.S., Hisjam, M., Yuniaristanto, Kurniawan, B.: An agri-food supply chain model for cultivating the capabilities of farmers in accessing capital using corporate social responsibility program. In: Proceedings of the International MultiConference of Engineers and Computer Scientists, pp. 877–882 (2015)Jiménez, M., Arenas, M., Bilbao, A., Rodríguez, M.V.: Linear programming with fuzzy parameters: an interactive method resolution. Eur. J. Oper. Res. 177, 1599–1609 (2007)Peidro, D., Mula, J., Jiménez, M., Botella, M.M.: A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment. Eur. J. Oper. Res. 205, 65–80 (2010)Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for managing uncertainty in a collaborative agri-food supply chain context. In: Camarinha-Matos, Luis M., Afsarmanesh, H., Fornasiero, R. (eds.) PRO-VE 2017. IFIP AICT, vol. 506, pp. 715–724. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65151-4_6

Hidden cusps

International audienceThis paper investigates a situation pointed out in a recent paper, in which a non-singular change of assembly mode of a planar 2-RPR-PR parallel manipulator was realized by encircling a point of multiplicity 4. It is shown that this situation is, in fact, a non-generic one and gives rise to cusps under a small perturbation. Furthermore , we show that, for a large class of singularities of multiplicity 4, there are only two types of stable singularities occurring in a small perturbation: these two types are given by the complex square mapping and the quarto mapping. Incidentally , this paper confirms the fact that, generically, a local non-singular change of solution must be accomplished by encircling a cusp point

Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

[EN] Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find a solution (vehicle routes) that minimizes the total time spent in servicing the required arcs. However, due to uncertainty, other characteristics of the solution are also considered. In particular, we illustrate how reliability concepts can enrich the probabilistic information given to decision-makers. In order to solve the aforementioned optimization problem, we extend the concept of simheuristic framework so it can also include fuzzy elements. Hence, both stochastic and fuzzy uncertainty are simultaneously incorporated into the CARP. In order to test our approach, classical CARP instances have been adapted and extended so that customers' demands become either stochastic or fuzzy. The experimental results show the effectiveness of the proposed approach when compared with more traditional ones. In particular, our fuzzy simheuristic is capable of generating new best-known solutions for the stochastic versions of some instances belonging to the tegl, tcarp, val, and rural benchmarks.Spanish Ministry of Science, Grant/Award Number: PID2019-111100RB-C21/AEI/10.13039/501100011033; Barcelona Council and the "la Caixa" Foundation under the framework of the Barcelona Science Plan 2020-2023, Grant/Award Number: 21S09355-001; Generalitat Valenciana,Grant/Award Number: PROMETEO/2021/065Martín, XA.; Panadero, J.; Peidro Payá, D.; Pérez Bernabeu, E.; Juan-Pérez, ÁA. (2023). Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times. Networks. 82(4):318-335. https://doi.org/10.1002/net.2215931833582

Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find a solution (vehicle routes) that minimizes the total time spent in servicing the required arcs. However, due to uncertainty, other characteristics of the solution are also considered. In particular, we illustrate how reliability concepts can enrich the probabilistic information given to decision-makers. In order to solve the aforementioned optimization problem, we extend the concept of simheuristic framework so it can also include fuzzy elements. Hence, both stochastic and fuzzy uncertainty are simultaneously incorporated into the CARP. In order to test our approach, classical CARP instances have been adapted and extended so that customers' demands become either stochastic or fuzzy. The experimental results show the effectiveness of the proposed approach when compared with more traditional ones. In particular, our fuzzy simheuristic is capable of generating new best-known solutions for the stochastic versions of some instances belonging to the tegl, tcarp, val, and rural benchmarks.This work has been partially supported by the Spanish Ministry of Science (PID2019-111100RB-C21/AEI/10.13039/01100011033), as well as by the Barcelona Council and the “laCaixa” Foundation under the framework of the Barcelona Science Plan 2020-2023 (grant21S09355-01) and Generalitat Valenciana (PROMETEO/2021/065).Peer ReviewedPostprint (published version

Application of stochastic programming to reduce uncertainties in quality-based supply planning of slaughterhouses

To match products of different quality with end market preferences under supply uncertainty, it is crucial to integrate product quality information in logistics decision making. We present a case of this integration in a meat processing company that faces uncertainty in delivered livestock quality. We develop a stochastic programming model that exploits historical product quality delivery data to produce slaughterhouse allocation plans with reduced levels of uncertainty in received livestock quality. The allocation plans generated by this model fulfil demand for multiple quality features at separate slaughterhouses under prescribed service levels while minimizing transportation costs. We test the model on real world problem instances generated from a data set provided by an industrial partner. Results show that historical farmer delivery data can be used to reduce uncertainty in quality of animals to be delivered to slaughterhouses

Supply Chain Intelligence

This chapter provides on overall picture of business intelligence (BI) and supply chain analytics (SCA) as a means to support supply chain management (SCM) and decision-making. Based on the literature review, we clarify the needs of BI and performance measurement in the SCM sphere, and discuss its potential to enhance decision-making in strategic, tactical and operational levels. We also make a closer look in to SCA in different areas and functions of SCM. Our findings indicate that the main challenge for harnessing the full potential of SCA is the lack of holistic and integrated BI approaches that originates from the fact that each functional area is using its own IT applications without necessary integration in to the company’s overall BI system. Following this examination, we construct a holistic framework that illustrates how an integrated, managerially planned BI system can be developed. Finally, we discuss the main competency requirements, as well as the challenges still prohibiting the great majority of firms from building smart and comprehensive BI systems for SCM.fi=vertaisarvioitu|en=peerReviewed

Bladder cancer index: cross-cultural adaptation into Spanish and psychometric evaluation

BACKGROUND: The Bladder Cancer Index (BCI) is so far the only instrument applicable across all bladder cancer patients, independent of tumor infiltration or treatment applied. We developed a Spanish version of the BCI, and assessed its acceptability and metric properties. METHODS: For the adaptation into Spanish we used the forward and back-translation method, expert panels, and cognitive debriefing patient interviews. For the assessment of metric properties we used data from 197 bladder cancer patients from a multi-center prospective study. The Spanish BCI and the SF-36 Health Survey were self-administered before and 12 months after treatment. Reliability was estimated by Cronbach's alpha. Construct validity was assessed through the multi-trait multi-method matrix. The magnitude of change was quantified by effect sizes to assess responsiveness. RESULTS: Reliability coefficients ranged 0.75-0.97. The validity analysis confirmed moderate associations between the BCI function and bother subscales for urinary (r = 0.61) and bowel (r = 0.53) domains; conceptual independence among all BCI domains (r ≤ 0.3); and low correlation coefficients with the SF-36 scores, ranging 0.14-0.48. Among patients reporting global improvement at follow-up, pre-post treatment changes were statistically significant for the urinary domain and urinary bother subscale, with effect sizes of 0.38 and 0.53. CONCLUSIONS: The Spanish BCI is well accepted, reliable, valid, responsive, and similar in performance compared to the original instrument. These findings support its use, both in Spanish and international studies, as a valuable and comprehensive tool for assessing quality of life across a wide range of bladder cancer patients

Solving NP-Hard Challenges in Logistics and Transportation under General Uncertainty Scenarios Using Fuzzy Simheuristics

In the field of logistics and transportation (L&T), this paper reviews the utilization of simheuristic algorithms to address NP-hard optimization problems under stochastic uncertainty. Then, the paper explores an extension of the simheuristics concept by introducing a fuzzy layer to tackle complex optimization problems involving both stochastic and fuzzy uncertainties. The hybrid approach combines simulation, metaheuristics, and fuzzy logic, offering a feasible methodology to solve large-scale NP-hard problems under general uncertainty scenarios. These scenarios are commonly encountered in L&T optimization challenges, such as the vehicle routing problem or the team orienteering problem, among many others. The proposed methodology allows for modeling various problem components-including travel times, service times, customers' demands, or the duration of electric batteries-as deterministic, stochastic, or fuzzy items. A cross-problem analysis of several computational experiments is conducted to validate the effectiveness of the fuzzy simheuristic methodology. Being a flexible methodology that allows us to tackle NP-hard challenges under general uncertainty scenarios, fuzzy simheuristics can also be applied in fields other than L&T