Abstract
The paper is concerned with using computational intelligence for identifying the relationships between variables and constraint programming for searching variants of completing a new product development project. The relationships are used to the cost estimation of new product development (NPD) and to the search for possible variants of reaching the desirable NPD cost. The main contribution of this paper is the use of constraint programming to a project prototyping problem in the context of product development. Moreover, the paper presents a method for estimating the NPD cost and searching variants that can ensure the desirable NPD cost. The project prototyping problem is formulated in terms of a constraint satisfaction problem and implemented using constraint programming techniques. These techniques enable declarative description of the considered problem and effective search strategies for finding admissible solutions. An example illustrates the applicability of the proposed approach for solving an NPD project prototyping problem.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Frühwirth, T., Abdennadher, S.: Essentials of Constraint Programming. Cognitive Technologies. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-662-05138-2
Liu, S.S., Wang, C.J.: Optimizing project selection and scheduling problems with time-dependent resource constraints. Autom. Constr. 20, 1110–1119 (2011)
Apt, K.R.: Principles of Constraint Programming. Cambridge University Press, Cambridge (2003)
Banaszak, Z., Zaremba, M., Muszyński, W.: Constraint programming for project-driven manufacturing. Int. J. Prod. Econ. 120, 463–475 (2009)
Baptiste, P., Le Pape, C., Nuijten, W.: Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems. Kluwer Academic Publishers, Norwell (2001)
Bocewicz, G., Nielsen, I.E., Banaszak, Z.: Production flows scheduling subject to fuzzy processing time constraints. Int. J. Comput. Integr. Manuf. 29, 1105–1127 (2016)
Do, M., Kambhampati, S.: Planning as constraint satisfaction: solving the planning graph by compiling it into CSP. Artif. Intell. 132, 151–182 (2001)
Relich, M.: Identifying project alternatives with the use of constraint programming. In: Borzemski, L., Grzech, A., Świątek, J., Wilimowska, Z. (eds.) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I. AISC, vol. 521, pp. 3–13. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-46583-8_1
Banaszak, Z.A.: CP-based decision support for project driven manufacturing. In: Józefowska, J., Weglarz, J. (eds.) Perspectives in Modern Project Scheduling. ISOR, vol. 92, pp. 409–437. Springer, Boston (2006). https://doi.org/10.1007/978-0-387-33768-5_16
Soto, R., Kjellerstrand, H., Gutiérrez, J., López, A., Crawford, B., Monfroy, E.: Solving manufacturing cell design problems using constraint programming. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds.) IEA/AIE 2012. LNCS (LNAI), vol. 7345, pp. 400–406. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31087-4_42
Modi, P.J., Jung, H., Tambe, M., Shen, W.-M., Kulkarni, S.: A dynamic distributed constraint satisfaction approach to resource allocation. In: Walsh, T. (ed.) CP 2001. LNCS, vol. 2239, pp. 685–700. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-45578-7_56
Sitek, P., Wikarek, J.: A multi-level approach to ubiquitous modeling and solving constraints in combinatorial optimization problems in production and distribution. Appl. Intell. 48(5), 1344–1367 (2018)
Grzybowska, K., Kovács, G.: The modelling and design process of coordination mechanisms in the supply chain. J. Appl. Logic 24, 25–38 (2017)
Liu, H., Gopalkrishnan, V., Quynh, K.T., Ng, W.K.: Regression models for estimating product life cycle cost. J. Intell. Manuf. 20(4), 401–408 (2009)
Nielsen, P., Jiang, L., Rytter, N.G., Chen, G.: An investigation of forecast horizon and observation fit’s influence on an econometric rate forecast model in the liner shipping industry. Marit. Policy Manag. 41(7), 667–682 (2014)
Seo, K.K., Park, J.H., Jang, D.S., Wallace, D.: Approximate estimation of the product life cycle cost using artificial neural networks in conceptual design. Int. J. Adv. Manuf. Technol. 19(6), 461–471 (2002)
Relich, M.: A knowledge-based system for new product portfolio selection. In: Różewski, P., Novikov, D., Bakhtadze, N., Zaikin, O. (eds.) New Frontiers in Information and Production Systems Modelling and Analysis. ISRL, vol. 98, pp. 169–187. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-23338-3_8
Kłosowski, G., Gola, A.: Risk-based estimation of manufacturing order costs with artificial intelligence. In: Federated Conference on Computer Science and Information Systems, pp. 729–732 (2016)
Efendigil, T., Önüt, S., Kahraman, C.: A decision support system for demand forecasting with artificial neural networks and neuro-fuzzy models: a comparative analysis. Expert Syst. Appl. 36(3), 6697–6707 (2009)
Relich, M., Bzdyra, K.: Knowledge discovery in enterprise databases for forecasting new product success. In: Jackowski, K., Burduk, R., Walkowiak, K., Woźniak, M., Yin, H. (eds.) IDEAL 2015. LNCS, vol. 9375, pp. 121–129. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24834-9_15
Van Roy, P.: Multiparadigm Programming in Mozart/Oz. LNCS, vol. 3389. Springer, Heidelberg (2005). https://doi.org/10.1007/b106627
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Relich, M., Nielsen, I., Bocewicz, G., Banaszak, Z. (2020). Constraint Programming for New Product Development Project Prototyping. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-42058-1_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-42057-4
Online ISBN: 978-3-030-42058-1
eBook Packages: Computer ScienceComputer Science (R0)