Decision making with Dempster-Shafer belief structure and the OWAWA operator

[EN] A new decision making model that uses the weighted average and the ordered weighted averaging (OWA) operator in the Dempster-Shafer belief structure is presented. Thus, we are able to represent the decision making problem considering objective and subjective information and the attitudinal character of the decision maker. For doing so, we use the ordered weighted averaging ¿ weighted average (OWAWA) operator. It is an aggregation operator that unifies the weighted average and the OWA in the same formulation. This approach is generalized by using quasi-arithmetic means and group decision making techniques. An application of the new approach in a group decision making problem concerning political management of a country is also developed.We would like to thank the anonymous reviewers for valuable comments that have improved the quality of the paper. Support from the Spanish Ministry of Education under project JC2009-00189 , the University of Barcelona (099311) and the European Commission (PIEFGA-2011-300062) is gratefully acknowledgedMerigó, JM.; Engemann, KJ.; Palacios Marqués, D. (2013). Decision making with Dempster-Shafer belief structure and the OWAWA operator. Technological and Economic Development of Economy. 19(sup 1):S100-S118. https://doi.org/10.3846/20294913.2013.869517SS100S11819sup 1Antuchevičienė, J., Zavadskas, E. K., & Zakarevičius, A. (2010). MULTIPLE CRITERIA CONSTRUCTION MANAGEMENT DECISIONS CONSIDERING RELATIONS BETWEEN CRITERIA / DAUGIATIKSLIAI STATYBOS VALDYMO SPRENDIMAI ATSIŽVELGIANT Į RODIKLIŲ TARPUSAVIO PRIKLAUSOMYBĘ. Technological and Economic Development of Economy, 16(1), 109-125. doi:10.3846/tede.2010.07Brauers, W. K. M., & Zavadskas, E. K. (2010). PROJECT MANAGEMENT BY MULTIMOORA AS AN INSTRUMENT FOR TRANSITION ECONOMIES / PROJEKTŲ VADYBA SU MULTIMOORA KAIP PRIEMONĖ PEREINAMOJO LAIKOTARPIO ŪKIAMS. 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PROBABILISTIC AGGREGATION OPERATORS AND THEIR APPLICATION IN UNCERTAIN MULTI-PERSON DECISION-MAKING / TIKIMYBINIAI SUMAVIMO OPERATORIAI IR JŲ TAIKYMAS PRIIMANT GRUPINIUS SPRENDIMUS NEAPIBRĖŽTOJE APLINKOJE. Technological and Economic Development of Economy, 17(2), 335-351. doi:10.3846/20294913.2011.584961Podvezko, V. (2009). Application of AHP technique. Journal of Business Economics and Management, 10(2), 181-189. doi:10.3846/1611-1699.2009.10.181-189Reformat, M., & Yager, R. R. (2007). Building ensemble classifiers using belief functions and OWA operators. Soft Computing, 12(6), 543-558. doi:10.1007/s00500-007-0227-2Srivastava, R. P., & Mock, T. J. (Eds.). (2002). Belief Functions in Business Decisions. Studies in Fuzziness and Soft Computing. doi:10.1007/978-3-7908-1798-0Torra, V. (1997). The weighted OWA operator. International Journal of Intelligent Systems, 12(2), 153-166. doi:10.1002/(sici)1098-111x(199702)12:23.0.co;2-pWei, G.-W. (2011). 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Uncertain generalized aggregation operators. Expert Systems with Applications, 39(1), 1105-1117. doi:10.1016/j.eswa.2011.07.11

Structure Adaptation in Stochastic Inverse Methods for Integrating Information

[EN] The use of inverse modeling techniques has greatly increased during the past several years because the advances in numerical modeling and increased computing power. Most of these methods require an a priori definition of the stochastic structure of conductivity (K) fields that is inferred only from K measurements. Therefore, the additional conditioning data, that implicitly integrate information not captured by K data, might lead to changes in the a priori model. Different inverse methods allow different degrees of structure adaptation to the whole set of data during the conditioning procedure. This paper illustrates the application of a powerful stochastic inverse method, the Gradual Conditioning (GC) method, to two different sets of data, both non-multiGaussian. One is based on a 2D synthetic aquifer and another on a real-complex case study, the Macrodispersion Experiment (MADE-2), site on Columbus Air Force Base in Mississippi (USA). We have analyzed how additional data change the a priori model on account of the perturbations performed when constraining stochastic simulations to data. Results show how the GC method tends to honour the a priori model in the synthetic case, showing fluctuations around it for the different simulated fields. However, in the 3D real case study, it is shown how the a priori structure is slightly modified not obeying just to fluctuations but possibly to the effect of the additional information on K, implicit in piezometric and concentration data. We conclude that implementing inversion methods able to yield a posteriori structure that incorporate more data might be of great importance in real cases in order to reduce uncertainty and to deal with risk assessment projects.Llopis Albert, C.; Merigó, JM.; Palacios Marqués, D. (2015). Structure Adaptation in Stochastic Inverse Methods for Integrating Information. Water Resources Management. 29(1):95-107. doi:10.1007/s11269-014-0829-2S95107291Abolverdi J, Khalili D (2010) Development of regional rainfall annual maxima for Southwestern Iran by LMoments. Water Resour Manag 24(11):2501–2526Adams EE, Gelhar LW (1992) Field study of dispersion in a heterogeneous aquifer 2. Spatial moments analysis. Water Resour Res 28(12):3293–3307Boggs JM, Adams EE (1992) Field study of dispersion in a heterogeneous aquifer. 4. Investigation of adsorption and sampling bias. Water Resour Res 28(12):3325–3336Boggs JM, Young SC, Beard LM (1992) Field study of dispersion in a heterogeneous aquifer. 1. Overview and site description. Water Resour Res 28(12):3281–3291Caers J (2007) Comparing the gradual deformation with the probability perturbation method for solving inverse problems. Math Geol 39(1). doi:10.1007/s11004-006-9064-6Capilla JE, Llopis-Albert C (2009) Gradual conditioning of non-Gaussian transmissivity fields to flow and mass transport data: 1. Theory. J Hydrol 371:66–74Carrera J, Alcolea A, Medina A, Hidalgo J, Slooten LJ (2005) Inverse problem in hydrogeology. J Hydrogeol 13:206–222Charalambous J, Rahman A, Carroll D (2013) Application of Monte Carlo simulation technique to design flood estimation: a case study for North Johnstone River in Queensland, Australia. Water Resour Manag 27:4099–4111. doi: 10.1007/s11269-013-0398-9De Marsily G, Delhomme JP, Coudrain-Ribstein A, Lavenue AM (2000) Four decades of inverse problems in hydrogeology. Geol Soc Am (Special Paper 348)Doherty J (1994) PEST: Corinda, Australia. Watermark Computing, 122 pGómez-Hernández JJ, Srivastava RM (1990) ISIM3D: An ANSI-C three dimensional multiple indicator conditional simulation program. Comput Geosci 16(4):395–440Gómez-Hernández JJ, Wen XH (1998) To be or not to be multiGaussian? A reflection on stochastic hydrogeology. Adv Water Resour 21(1):47–61Gómez-Hernández JJ, Sahuquillo A, Capilla JE (1997) Stochastic simulation of transmissivity fields conditional to both transmissivity and piezometric data. 1. Theory. J Hydrol 203:162–174Hu LY (2000) Gradual deformation and iterative calibration of gaussian-related stochastic models. Math Geol 32(1):87–108Llopis-Albert C, Capilla JE (2009a) Gradual conditioning of non-gaussian transmissivity fields to flow and mass transport Data: 3. Application to the Macrodispersion experiment (MADE-2) site, on Columbus air force base in Mississippi (USA). J Hydrol 371:75–84Llopis-Albert C, Capilla JE (2009b) Gradual conditioning of non-Gaussian transmissivity fields to flow and mass transport data: 2. Demonstration on a synthetic aquifer. J Hydrol 371:53–65Llopis-Albert C, Capilla JE (2010a) Stochastic inverse modeling of hydraulic conductivity fields taking into account independent stochastic structures: a 3D case study. J Hydrol 391:277–288Llopis-Albert C, Capilla JE (2010b) Stochastic simulation of non-Gaussian 3D conductivity fields in a fractured medium with multiple statistical populations: a case study. J Hydrol Eng 15(7):554–566Llopis-Albert C., Capilla JE (2011) Change of the a priori stochastic structure in the conditional simulation of transmissivity fields. P.M. Atkinson and C.D. Lloyd (eds.), geoENV VII – Geostatistics for Environmental Applications, Quant Geol Geostat 16. Springer. ISBN: 9048123216Llopis-Albert C, Palacios-Marqués D, Merigó JM (2014) A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty. J Hydrol 511:10–16. doi: 10.1016/j.jhydrol.2014.01.021McLaughlin D, Townley LR (1996) A reassessment of the groundwater inverse problem. 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Primary pleural myxoid liposarcoma: case report and literature review

Myxoid liposarcoma is a histological subtype of malignant tumors within the group of sarcomas. It is more common in men between the ages of 40 and 50 years. Diagnosis is difficult because they are usually asymptomatic lesions, computed tomography (CT) scan and magnetic resonance are the studies of choice. The gold of treatment is surgical resection with free margins. Chemotherapy and radiotherapy have shown a good response. A 46-year-old male was detected incidental mediastinal lesion by radiography, CT scan showed a hypodense lesion in the right hemithorax that extended to the left hemithorax, infiltrating the diaphragm and large vessels. The patient underwent an exploratory thoracotomy, finding a multilobulated tumor and mucous content approximately 600 ml, adjacent structures were infiltrated, so complete resection was not possible. Subsequently, adjuvant chemotherapy given. The histopathological diagnosis was myxoid liposarcoma. Myxoid liposarcoma is a malignant lesion. The primary pleural origin is rare. Surgical resection with free margins has a good prognosis. Due to advanced disease, a complete resection in this case was not possible, that compromised the patient prognosis

Crowdlending: mapping the core literature and research frontiers

[EN] Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the future.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Ribeiro-Navarrete, S.; Piñeiro-Chousa, J.; López-Cabarcos, MÁ.; Palacios Marqués, D. (2022). Crowdlending: mapping the core literature and research frontiers. Review of Managerial Science. 16(8):2381-2411. https://doi.org/10.1007/s11846-021-00491-82381241116

Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector

[EN] Lack of homogeneity in the product (LHP) is a problem when customers require homogeneous units of a single product. In such cases, the optimal allocation of inventory to orders becomes much more complex. Furthermore, in an MTS environment, an optimal initial allocation may become less than ideal over time, due to different circumstances. This problem occurs in the ceramics sector, where the final product varies in tone and calibre. This paper proposes a methodology for the reallocation of inventory to orders in LHP situation (MERIO-LHP) and a model-based decision-support system (DSS) to support the methodology, which enables an optimal reallocation of inventory to order lines to be carried out in real businesses environments in which LHP is inherent. The proposed methodology and model-based DSS were validated by applying it to a real case at a ceramics company. The analysis of the results indicates that considerable improvements can be obtained with regard to the quantity of orders fulfilled and sales turnover.Oltra Badenes, RF.; Gil Gómez, H.; Merigó, JM.; Palacios Marqués, D. (2019). Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector. PLoS ONE. 14(7):1-19. https://doi.org/10.1371/journal.pone.0219433S119147Alarcón, F., Alemany, M. M. E., Lario, F. C., & Oltra, R. F. (2011). La falta de homogeneidad del producto (FHP) en las empresas cerámicas y su impacto en la reasignación del inventario. Boletín de la Sociedad Española de Cerámica y Vidrio, 50(1), 49-58. doi:10.3989/cyv.072011Wanke, P., Alvarenga, H., Correa, H., Hadi-Vencheh, A., & Azad, M. A. K. (2017). Fuzzy inference systems and inventory allocation decisions: Exploring the impact of priority rules on total costs and service levels. 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Expert Systems with Applications, 41(1), 39-49. doi:10.1016/j.eswa.2013.07.009Protopappa-Sieke, M., Sieke, M. A., & Thonemann, U. W. (2016). Optimal two-period inventory allocation under multiple service level contracts. European Journal of Operational Research, 252(1), 145-155. doi:10.1016/j.ejor.2016.01.013Luo, K., Bollapragada, R., & Kerbache, L. (2017). Inventory allocation models for a two-stage, two-product, capacitated supplier and retailer problem with random demand. International Journal of Production Economics, 187, 168-181. doi:10.1016/j.ijpe.2016.12.014Zhao, H., Huang, E., Dou, R., & Wu, K. (2019). A multi-objective production planning problem with the consideration of time and cost in clinical trials. Expert Systems with Applications, 124, 25-38. doi:10.1016/j.eswa.2019.01.038Kang, K., Pu, W., Ma, Y., & Wang, X. (2018). Bi-objective inventory allocation planning problem with supplier selection and carbon trading under uncertainty. 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