Fuzzy multi-objective optimisation for master planning in a ceramic supply chain

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/10.1080/00207543.2011.588267S301130205011Alemany, 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), 5053–5074Beamon, B. M. (1998). Supply chain design and analysis: International Journal of Production Economics, 55(3), 281-294. doi:10.1016/s0925-5273(98)00079-6Chen, 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. doi:10.1016/j.compchemeng.2003.09.014Chern, C.-C., & Hsieh, J.-S. (2007). A heuristic algorithm for master planning that satisfies multiple objectives. Computers & Operations Research, 34(11), 3491-3513. doi:10.1016/j.cor.2006.02.022Kreipl, S., & Pinedo, M. (2009). Planning and Scheduling in Supply Chains: An Overview of Issues in Practice. Production and Operations Management, 13(1), 77-92. doi:10.1111/j.1937-5956.2004.tb00146.xLai, Y.-J., & Hwang, C.-L. (1993). Possibilistic linear programming for managing interest rate risk. Fuzzy Sets and Systems, 54(2), 135-146. doi:10.1016/0165-0114(93)90271-iLi, X., Zhang, B., & Li, H. (2006). Computing efficient solutions to fuzzy multiple objective linear programming problems. Fuzzy Sets and Systems, 157(10), 1328-1332. doi:10.1016/j.fss.2005.12.003Mula, J., Peidro, D., Díaz-Madroñero, M., & Vicens, E. (2010). Mathematical programming models for supply chain production and transport planning. European Journal of Operational Research, 204(3), 377-390. doi:10.1016/j.ejor.2009.09.008Mula, J., Peidro, D., and Poler, R., 2010b. The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand.International Journal of Production Economics, In pressPark *, Y. B. (2005). An integrated approach for production and distribution planning in supply chain management. International Journal of Production Research, 43(6), 1205-1224. doi:10.1080/00207540412331327718Peidro, D., Mula, J., Poler, R., & Lario, F.-C. (2008). Quantitative models for supply chain planning under uncertainty: a review. The International Journal of Advanced Manufacturing Technology, 43(3-4), 400-420. doi:10.1007/s00170-008-1715-yPeidro, D., Mula, J., Poler, R., & Verdegay, J.-L. (2009). Fuzzy optimization for supply chain planning under supply, demand and process uncertainties. Fuzzy Sets and Systems, 160(18), 2640-2657. doi:10.1016/j.fss.2009.02.021Selim, H., Araz, C., & Ozkarahan, I. (2008). Collaborative production–distribution planning in supply chain: A fuzzy goal programming approach. Transportation Research Part E: Logistics and Transportation Review, 44(3), 396-419. doi:10.1016/j.tre.2006.11.001Selim, H., & Ozkarahan, I. (2006). A supply chain distribution network design model: An interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418. doi:10.1007/s00170-006-0842-6Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214. doi:10.1016/j.fss.2007.08.010Haehling von Lanzenauer, C., & Pilz-Glombik, K. (2002). Coordinating supply chain decisions: an optimization model. OR Spectrum, 24(1), 59-78. doi:10.1007/s291-002-8200-3Zimmermann, H.-J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1(1), 45-55. doi:10.1016/0165-0114(78)90031-

Hölderlin en Riba : travessar el cant, traspassar la llengua

Des de la traducció que Carles Riba va fer de la poesia Friedrich Hölderlin, s'obre la possibilitat de commoure l'estatut acceptat de la traducció i, també, de la pròpia llengua. Parant esment, doncs, a la constel·lació dibuixada pels plantejaments al voltant de la poesia i el llenguatge de Riba, de Hölderlin i de Vossler, i prenent com a guia la noció de ritme, a més d'albirar l'impacte de la figura de Hölderlin en l'obra ribiana, cal fer aquesta commoció que esdevé, potser, una obertura de l'espai mateix de la poesia.From the translation of Friedrich Hölderlin's poetry by Carles Riba, the possibility is opened to move the status of the translation and of the language itself. Attending, then, to the constellation drawn by the approaches to the language and poetry of Riba, Hölderlin and Vossler, and accepting as a guide the notion of «rhythm», as well as verifying the impact of Hölderlin's poetry on Riba's work, it is necessary to make effective this shock that perhaps becomes the opening of the space of poetry itself

Ritme, escriptura i traducció en Hölderlin. Tot no és altra cosa més que ritme

En el número 57 de la revista L'Espill trobaràs un dossier monogràfic sobre "La política cultural al País Valencià: una perspectiva crítica", amb contribucions de Joaquim Rius Ulldemolins, Sandra Obiol, Pau Alabajos, Adolf Beltran i Àfrica Ramirez. A més, articles d'Ernest Garcia, Enric Marin, Joan Manuel Tresserras, Ignacio Sánchez-Cuenca, Josep Pérez i Paola Lo Cascio, així com documents de Mohandas Gandhi i un full de dietari de Mireia Sallarès

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Reinforcement learning applied to production planning and control

[EN] The objective of this paper is to examine the use and applications of reinforcement learning (RL) techniques in the production planning and control (PPC) field addressing the following PPC areas: facility resource planning, capacity planning, purchase and supply management, production scheduling and inventory management. The main RL characteristics, such as method, context, states, actions, reward and highlights, were analysed. The considered number of agents, applications and RL software tools, specifically, programming language, platforms, application programming interfaces and RL frameworks, among others, were identified, and 181 articles were sreviewed. The results showed that RL was applied mainly to production scheduling problems, followed by purchase and supply management. The most revised RL algorithms were model-free and single-agent and were applied to simplified PPC environments. Nevertheless, their results seem to be promising compared to traditional mathematical programming and heuristics/metaheuristics solution methods, and even more so when they incorporate uncertainty or non-linear properties. Finally, RL value-based approaches are the most widely used, specifically Q-learning and its variants and for deep RL, deep Q-networks. In recent years however, the most widely used approach has been the actor-critic method, such as the advantage actor critic, proximal policy optimisation, deep deterministic policy gradient and trust region policy optimisation.The funding for the research work that has led to the obtained results came from the following grants: CADS4.0 (Ref. RTI2018-101344-B-I00) and NIOTOME (Ref. RTI2018102020-B-I00), financed byMCIN/AEI/10.13039/501100011033 and 'ERDF A way of making DEurope'; the EU H2020 research and innovation programme with grant numbers 825631 'Zero-Defect Manufacturing Platform (ZDMP)' and 958205 'Industrial Data Services for Quality Control in SmartManufacturing (i4Q)'; 'Industrial Production and Logistics Optimization in Industry 4.0' (i4OPT) (Ref. PROMETEO/2021/065) and 'Resilient, Sustainable and PeopleOriented Supply Chain 5.0 Optimization Using Hybrid Intelligence' (RESPECT) (Ref. CIGE/2021/159) Projects were funded by the Generalitat Valenciana (Valencian Regional Government).Esteso, A.; Peidro Payá, D.; Mula, J.; Díaz-Madroñero Boluda, FM. (2023). Reinforcement learning applied to production planning and control. International Journal of Production Research. 61(16):5772-5789. https://doi.org/10.1080/00207543.2022.210418057725789611

A Conceptual Model for Integrating Transport Planning: MRP IV

In this article, a conceptual model, called MRP IV, is proposed in order to serve as a reference to develop a new production technology that integrates material planning decisions, production resource capacities and supply chain transport for the purpose of avoiding the suboptimization of these plans which, today, are usually generated sequentially and independently. This article aim is twofold: (1) it identifies the advances and deficiencies in the MRP calculations, mainly based on the dynamic multi-level capacitated lot-sizing problem (MLCLSP); and (2) it proposes a conceptual model, defining the inputs, outputs, modeling and solution approaches, to overcome the deficiencies identified in current MRP systems and act as a baseline to propose resolution models and algorithms required to develop MRP IV as a decision-making system. © 2012 IFIP International Federation for Information Processing. Mula, J.; Díaz-Madroñero Boluda, FM.; Peidro Payá, D. (2012). A conceptual model for integrating transport planning: MRP IV. En IFIP Advances in Information and Communication Technology. Springer. (384):54-65. doi:10.1007/978-3-642-33980-6_7 Senia 54 65 384 Document type: Part of book or chapter of boo

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