AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Sustainability assessment of concrete bridge deck designs in coastal environments using neutrosophic criteria weights

"This is an Accepted Manuscript of an article published by Taylor & Francis in Structure and Infrastructure Engineering on 02/07/2020, available online: https://doi.org/10.1080/15732479.2019.1676791."[EN] Essential infrastructures such as bridges are designed to provide a long-lasting and intergenerational functionality. In those cases, sustainability becomes of paramount importance when the infrastructure is exposed to aggressive environments, which can jeopardise their durability and lead to significant maintenance demands. The assessment of sustainability is however often complex and uncertain. The present study assesses the sustainability performance of 16 alternative designs of a concrete bridge deck in a coastal environment on the basis of a neutrosophic group analytic hierarchy process (AHP). The use of neutrosophic logic in the field of multi-criteria decision-making, as a generalisation of the widely used fuzzy logic, allows for a proper capture of the vagueness and uncertainties of the judgements emitted by the decision-makers. TOPSIS technique is then used to aggregate the different sustainability criteria. From the results, it is derived that only the simultaneous consideration of the economic, environmental and social life cycle impacts of a design shall lead to adequate sustainable designs. Choices made based on the optimality of a design in only some of the sustainability pillars will lead to erroneous conclusions. The use of concrete with silica fume has resulted in a sustainability performance of 46.3% better than conventional concrete designs.The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (Project: BIA2017-85098-R).Navarro, I.; Yepes, V.; Martí, J. (2020). Sustainability assessment of concrete bridge deck designs in coastal environments using neutrosophic criteria weights. Structure and Infrastructure Engineering. 16(7):949-967. https://doi.org/10.1080/15732479.2019.1676791S949967167Abdel-Basset, M., Manogaran, G., Mohamed, M., & Chilamkurti, N. (2018). Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem. Future Generation Computer Systems, 89, 19-30. doi:10.1016/j.future.2018.06.024Abdullah, L., & Najib, L. (2014). Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia. International Journal of Sustainable Energy, 35(4), 360-377. doi:10.1080/14786451.2014.907292Ali, M. S., Aslam, M. S., & Mirza, M. S. (2015). A sustainability assessment framework for bridges – a case study: Victoria and Champlain Bridges, Montreal. Structure and Infrastructure Engineering, 1-14. doi:10.1080/15732479.2015.1120754Allacker, K. (2012). Environmental and economic optimisation of the floor on grade in residential buildings. The International Journal of Life Cycle Assessment, 17(6), 813-827. doi:10.1007/s11367-012-0402-2Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96. doi:10.1016/s0165-0114(86)80034-3Barone, G., & Frangopol, D. M. (2014). Life-cycle maintenance of deteriorating structures by multi-objective optimization involving reliability, risk, availability, hazard and cost. Structural Safety, 48, 40-50. doi:10.1016/j.strusafe.2014.02.002Biswas, P., Pramanik, S., & Giri, B. C. (2015). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Computing and Applications, 27(3), 727-737. doi:10.1007/s00521-015-1891-2Bolturk, E., & Kahraman, C. (2018). A novel interval-valued neutrosophic AHP with cosine similarity measure. Soft Computing, 22(15), 4941-4958. doi:10.1007/s00500-018-3140-yBuckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233-247. doi:10.1016/0165-0114(85)90090-9Büyüközkan, G., & Göçer, F. (2017). Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Applied Soft Computing, 52, 1222-1238. doi:10.1016/j.asoc.2016.08.051Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36(5), 8900-8909. doi:10.1016/j.eswa.2008.11.046Chen, C., Habert, G., Bouzidi, Y., Jullien, A., & Ventura, A. (2010). LCA allocation procedure used as an incitative method for waste recycling: An application to mineral additions in concrete. Resources, Conservation and Recycling, 54(12), 1231-1240. doi:10.1016/j.resconrec.2010.04.001Chu, T.-C., & Tsao, C.-T. (2002). Ranking fuzzy numbers with an area between the centroid point and original point. Computers & Mathematics with Applications, 43(1-2), 111-117. doi:10.1016/s0898-1221(01)00277-2Cope, A., Bai, Q., Samdariya, A., & Labi, S. (2013). Assessing the efficacy of stainless steel for bridge deck reinforcement under uncertainty using Monte Carlo simulation. Structure and Infrastructure Engineering, 9(7), 634-647. doi:10.1080/15732479.2011.602418De la Fuente, A., Pons, O., Josa, A., & Aguado, A. (2016). Multi-Criteria Decision Making in the sustainability assessment of sewerage pipe systems. Journal of Cleaner Production, 112, 4762-4770. doi:10.1016/j.jclepro.2015.07.002Deli, I., & Şubaş, Y. (2016). A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems. International Journal of Machine Learning and Cybernetics, 8(4), 1309-1322. doi:10.1007/s13042-016-0505-3Dong, Y., Zhang, G., Hong, W.-C., & Xu, Y. (2010). Consensus models for AHP group decision making under row geometric mean prioritization method. Decision Support Systems, 49(3), 281-289. doi:10.1016/j.dss.2010.03.003Dubois, D. (2011). The role of fuzzy sets in decision sciences: Old techniques and new directions. Fuzzy Sets and Systems, 184(1), 3-28. doi:10.1016/j.fss.2011.06.003Eamon, C. D., Jensen, E. A., Grace, N. F., & Shi, X. (2012). Life-Cycle Cost Analysis of Alternative Reinforcement Materials for Bridge Superstructures Considering Cost and Maintenance Uncertainties. Journal of Materials in Civil Engineering, 24(4), 373-380. doi:10.1061/(asce)mt.1943-5533.0000398Enea, M., & Piazza, T. (2004). Project Selection by Constrained Fuzzy AHP. Fuzzy Optimization and Decision Making, 3(1), 39-62. doi:10.1023/b:fodm.0000013071.63614.3dGarcía-Segura, T., Penadés-Plà, V., & Yepes, V. (2018). Sustainable bridge design by metamodel-assisted multi-objective optimization and decision-making under uncertainty. Journal of Cleaner Production, 202, 904-915. doi:10.1016/j.jclepro.2018.08.177García-Segura, T., & Yepes, V. (2016). Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety. Engineering Structures, 125, 325-336. doi:10.1016/j.engstruct.2016.07.012García-Segura, T., Yepes, V., Frangopol, D. M., & Yang, D. Y. (2017). Lifetime reliability-based optimization of post-tensioned box-girder bridges. Engineering Structures, 145, 381-391. doi:10.1016/j.engstruct.2017.05.013Gervásio, H., & Simões da Silva, L. (2012). A probabilistic decision-making approach for the sustainable assessment of infrastructures. Expert Systems with Applications, 39(8), 7121-7131. doi:10.1016/j.eswa.2012.01.032Guzmán-Sánchez, S., Jato-Espino, D., Lombillo, I., & Diaz-Sarachaga, J. M. (2018). Assessment of the contributions of different flat roof types to achieving sustainable development. Building and Environment, 141, 182-192. doi:10.1016/j.buildenv.2018.05.063Heravi, G., Fathi, M., & Faeghi, S. (2017). Multi-criteria group decision-making method for optimal selection of sustainable industrial building options focused on petrochemical projects. Journal of Cleaner Production, 142, 2999-3013. doi:10.1016/j.jclepro.2016.10.168Invidiata, A., Lavagna, M., & Ghisi, E. (2018). Selecting design strategies using multi-criteria decision making to improve the sustainability of buildings. Building and Environment, 139, 58-68. doi:10.1016/j.buildenv.2018.04.041Jakiel, P., & Fabianowski, D. (2015). FAHP model used for assessment of highway RC bridge structural and technological arrangements. Expert Systems with Applications, 42(8), 4054-4061. doi:10.1016/j.eswa.2014.12.039Kahraman, C., Cebi, S., Onar, S. C., & Oztaysi, B. (2018). A novel trapezoidal intuitionistic fuzzy information axiom approach: An application to multicriteria landfill site selection. Engineering Applications of Artificial Intelligence, 67, 157-172. doi:10.1016/j.engappai.2017.09.009Kere, K. J., & Huang, Q. (2019). Life-Cycle Cost Comparison of Corrosion Management Strategies for Steel Bridges. Journal of Bridge Engineering, 24(4), 04019007. doi:10.1061/(asce)be.1943-5592.0001361Liang, R., Wang, J., & Zhang, H. (2017). A multi-criteria decision-making method based on single-valued trapezoidal neutrosophic preference relations with complete weight information. Neural Computing and Applications, 30(11), 3383-3398. doi:10.1007/s00521-017-2925-8Liu, P., & Liu, X. (2016). The neutrosophic number generalized weighted power averaging operator and its application in multiple attribute group decision making. International Journal of Machine Learning and Cybernetics, 9(2), 347-358. doi:10.1007/s13042-016-0508-0Martí, J. V., García-Segura, T., & Yepes, V. (2016). Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy. Journal of Cleaner Production, 120, 231-240. doi:10.1016/j.jclepro.2016.02.024Martínez-Blanco, J., Lehmann, A., Muñoz, P., Antón, A., Traverso, M., Rieradevall, J., & Finkbeiner, M. (2014). Application challenges for the social Life Cycle Assessment of fertilizers within life cycle sustainability assessment. Journal of Cleaner Production, 69, 34-48. doi:10.1016/j.jclepro.2014.01.044Mistry, M., Koffler, C., & Wong, S. (2016). LCA and LCC of the world’s longest pier: a case study on nickel-containing stainless steel rebar. The International Journal of Life Cycle Assessment, 21(11), 1637-1644. doi:10.1007/s11367-016-1080-2Moazami, D., Behbahani, H., & Muniandy, R. (2011). Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic. Expert Systems with Applications, 38(10), 12869-12879. doi:10.1016/j.eswa.2011.04.079Mosalam, K. M., Alibrandi, U., Lee, H., & Armengou, J. (2018). Performance-based engineering and multi-criteria decision analysis for sustainable and resilient building design. Structural Safety, 74, 1-13. doi:10.1016/j.strusafe.2018.03.005Navarro, I., Yepes, V., & Martí, J. (2018). Life Cycle Cost Assessment of Preventive Strategies Applied to Prestressed Concrete Bridges Exposed to Chlorides. Sustainability, 10(3), 845. doi:10.3390/su10030845Navarro, I. J., Martí, J. V., & Yepes, V. (2019). Reliability-based maintenance optimization of corrosion preventive designs under a life cycle perspective. Environmental Impact Assessment Review, 74, 23-34. doi:10.1016/j.eiar.2018.10.001Navarro, I. J., Yepes, V., & Martí, J. V. (2018). Social life cycle assessment of concrete bridge decks exposed to aggressive environments. Environmental Impact Assessment Review, 72, 50-63. doi:10.1016/j.eiar.2018.05.003Navarro, I. J., Yepes, V., Martí, J. V., & González-Vidosa, F. (2018). Life cycle impact assessment of corrosion preventive designs applied to prestressed concrete bridge decks. Journal of Cleaner Production, 196, 698-713. doi:10.1016/j.jclepro.2018.06.110Nogueira, C. G., Leonel, E. D., & Coda, H. B. (2012). Reliability algorithms applied to reinforced concrete structures durability assessment. Revista IBRACON de Estruturas e Materiais, 5(4), 440-450. doi:10.1590/s1983-41952012000400003Pamučar, D., Badi, I., Sanja, K., & Obradović, R. (2018). A Novel Approach for the Selection of Power-Generation Technology Using a Linguistic Neutrosophic CODAS Method: A Case Study in Libya. Energies, 11(9), 2489. doi:10.3390/en11092489Penadés-Plà, V., García-Segura, T., Martí, J., & Yepes, V. (2016). A Review of Multi-Criteria Decision-Making Methods Applied to the Sustainable Bridge Design. Sustainability, 8(12), 1295. doi:10.3390/su8121295Peng, J., Wang, J., & Yang, W.-E. (2016). A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems. International Journal of Systems Science, 48(2), 425-435. doi:10.1080/00207721.2016.1218975Petcherdchoo, A. (2015). Environmental Impacts of Combined Repairs on Marine Concrete Structures. Journal of Advanced Concrete Technology, 13(3), 205-213. doi:10.3151/jact.13.205PRASCEVIC, N., & PRASCEVIC, Z. (2017). APPLICATION OF FUZZY AHP FOR RANKING AND SELECTION OF ALTERNATIVES IN CONSTRUCTION PROJECT MANAGEMENT. Journal of Civil Engineering and Management, 23(8), 1123-1135. doi:10.3846/13923730.2017.1388278Pryn, M. R., Cornet, Y., & Salling, K. B. (2015). APPLYING SUSTAINABILITY THEORY TO TRANSPORT INFRASTRUCTURE ASSESSMENT USING A MULTIPLICATIVE AHP DECISION SUPPORT MODEL. TRANSPORT, 30(3), 330-341. doi:10.3846/16484142.2015.1081281Rashidi, M., Samali, B., & Sharafi, P. (2015). A new model for bridge management: Part B: decision support system for remediation planning. Australian Journal of Civil Engineering, 14(1), 46-53. doi:10.1080/14488353.2015.1092642Sabatino, S., Frangopol, D. M., & Dong, Y. (2015). Life cycle utility-informed maintenance planning based on lifetime functions: optimum balancing of cost, failure consequences and performance benefit. Structure and Infrastructure Engineering, 12(7), 830-847. doi:10.1080/15732479.2015.1064968Safi, M., Sundquist, H., & Karoumi, R. (2015). Cost-Efficient Procurement of Bridge Infrastructures by Incorporating Life-Cycle Cost Analysis with Bridge Management Systems. Journal of Bridge Engineering, 20(6), 04014083. doi:10.1061/(asce)be.1943-5592.0000673Sajedi, S., & Huang, Q. (2019). Reliability-based life-cycle-cost comparison of different corrosion management strategies. Engineering Structures, 186, 52-63. doi:10.1016/j.engstruct.2019.02.018Sierra, L. A., Pellicer, E., & Yepes, V. (2016). Social Sustainability in the Lifecycle of Chilean Public Infrastructure. Journal of Construction Engineering and Management, 142(5), 05015020. doi:10.1061/(asce)co.1943-7862.0001099Sierra, L. A., Yepes, V., García-Segura, T., & Pellicer, E. (2018). Bayesian network method for decision-making about the social sustainability of infrastructure projects. Journal of Cleaner Production, 176, 521-534. doi:10.1016/j.jclepro.2017.12.140Sodenkamp, M. A., Tavana, M., & Di Caprio, D. (2018). An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets. Applied Soft Computing, 71, 715-727. doi:10.1016/j.asoc.2018.07.020Stewart, M. G., Estes, A. C., & Frangopol, D. M. (2004). Bridge Deck Replacement for Minimum Expected Cost Under Multiple Reliability Constraints. Journal of Structural Engineering, 130(9), 1414-1419. doi:10.1061/(asce)0733-9445(2004)130:9(1414)Swarr, T. E., Hunkeler, D., Klöpffer, W., Pesonen, H.-L., Ciroth, A., Brent, A. C., & Pagan, R. (2011). Environmental life-cycle costing: a code of practice. The International Journal of Life Cycle Assessment, 16(5), 389-391. doi:10.1007/s11367-011-0287-5Tahmasebi Birgani, Y., & Yazdandoost, F. (2018). An Integrated Framework to Evaluate Resilient-Sustainable Urban Drainage Management Plans Using a Combined-adaptive MCDM Technique. Water Resources Management, 32(8), 2817-2835. doi:10.1007/s11269-018-1960-2Tesfamariam, S., & Sadiq, R. (2006). Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP). Stochastic Environmental Research and Risk Assessment, 21(1), 35-50. doi:10.1007/s00477-006-0042-9Wang, Y.-M., & Elhag, T. M. S. (2006). On the normalization of interval and fuzzy weights. Fuzzy Sets and Systems, 157(18), 2456-2471. doi:10.1016/j.fss.2006.06.008Yang, Z., Shi, X., Creighton, A. T., & Peterson, M. M. (2009). Effect of styrene–butadiene rubber latex on the chloride permeability and microstructure of Portland cement mortar. Construction and Building Materials, 23(6), 2283-2290. doi:10.1016/j.conbuildmat.2008.11.011Ye, J. (2013). Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. International Journal of General Systems, 42(4), 386-394. doi:10.1080/03081079.2012.761609Ye, J. (2017). Subtraction and Division Operations of Simplified Neutrosophic Sets. Information, 8(2), 51. doi:10.3390/info8020051Yepes, V., García-Segura, T., & Moreno-Jiménez, J. M. (2015). A cognitive approach for the multi-objective optimization of RC structural problems. Archives of Civil and Mechanical Engineering, 15(4), 1024-1036. doi:10.1016/j.acme.2015.05.001Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. doi:10.1016/s0019-9958(65)90241-xZadeh, L. A. (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3(1), 28-44. doi:10.1109/tsmc.1973.5408575Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016). Development of TOPSIS Method to Solve Complicated Decision-Making Problems — An Overview on Developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(03), 645-682. doi:10.1142/s021962201630001

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes