^[1] See G.A. Miller, “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information,” Psychological Review 63, no. 2 (1956): 81–97.

^[2] D. Selva and E. Crawley, “VASSAR: Value Assessment of System Architectures Using Rules.” In Aerospace Conference, 2013 IEEE (Big Sky, MN: IEEE, 2013).

^[3]The NEOSS example is based on substantial work by the authors on the architecture of Earth observing satellite systems. See, for example, D. Selva, B.G. Cameron, and E.F. Crawley, “Rule-based System Architecting of Earth Observing Systems: The Earth Science Decadal Survey,” Journal of Spacecraft and Rockets, 2014.

^[4]See discussion in D. Selva, “Rule-based System Architecting of Earth Observation Satellite ­Systems,” PhD dissertation, Massachusetts Institute of Technology (Ann Arbor: ProQuest/UMI, 2012), pp. 172–188.

^[5]C. Alexander, A Pattern Language: Towns, Buildings, Construction (Oxford University Press, 1977).

^[6]E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design Patterns: Elements of Reusable Object-­Oriented Software (Addison-Wesley Professional, 1994).

^[7]For a more extensive discussion of Patterns and styles, the interested reader can refer to F. Bushmann, R. Meunier, and H. Rohnert, Pattern-oriented Software Architecture: A System of Patterns (New York: Wiley, 1996) or M. Fowler, Patterns of Enterprise Application Architecture (Addison-Wesley Professional, 2002).

^[8]Note that in other references, architectural “Pattern” and “style” are considered synonyms designating the common structure seen in many problem instances. This is different from our definition, which reserves the word “Pattern” for the common problem structure and reserves the word “style” for the solutions. See, for example, N. Rozanski and E. Woods, Software Systems Architecture (Reading, MA: Addison-Wesley, 2012).

^[9] See, for example, M. Ehrgott and X. Gandibleux, “A Survey and Annotated Bibliography of Multiobjective Combinatorial Optimization,” OR Spectrum 22 (November 2000): 425–460.

^[10] Information on different AUV architectures can be found at http://oceanexplorer.noaa.gov/ and http://auvac.org/

^[11]Facebook announced in 2014 that it intends to deploy a network of 11,000 drones to provide Internet services to Africa.

^[12]Adapted from S.P. Ajemian, “Modeling and Evaluation of Aerial Layer Communications System ­Architectures,” Master’s thesis, Engineering Systems Division, Massachusetts Institute of Technology, 2012.

^[13]See, for example, D. Ferrucci, A. Levas, S. Bagchi, D. Gondek, and E.T. Mueller, “Watson: Beyond Jeopardy!” Artificial Intelligence, 2013, 199–200, 93–105. doi:10.1016/j.artint.2012.06.009.

^[14] See Schäfer’s dissertation: U. Schäfer, “Integrating Deep and Shallow Natural Language Processing Components: Representations and Hybrid Architectures, ” Universitat des Saarlandes, 2007.

^[15] See J.H. Holland, Adaptation in Natural and Artificial Systems (Cambridge, MA: MIT Press, 1992).

^[16] See, for example, the authors’ VASSAR formulation: D. Selva, and E. Crawley, “VASSAR: Value ­Assessment of System Architectures Using Rules.” In Aerospace Conference, 2013 IEEE (Big Sky, MN: IEEE, 2013).

^[17] See A. Dominguez-Garcia, G. Hanuschak, S. Hall, and E. Crawley, “A Comparison of GN&C ­Architectural Approaches for Robotic and Human-Rated Spacecraft,” AIAA Guidance, Navigation, and Control Conference and Exhibit, 2007, pp. 20–23.

^[18] See N. Suh, “Axiomatic Design Theory for Systems,” Research in Engineering Design 10, no. 4 (1998): 189–209.

^[19]As a side note, the number of partitions in a set of $m$ elements with exactly $k$ subsets is given by the Stirling numbers of the second kind, and the total number of partitions of a set is given by the Bell numbers, which are equal to the sum of all the Stirling numbers of the second kind for all possible values of $k$. Any combinatorics text will provide formulas for these numbers. See, for example, R. Grimaldi, ­Discrete and Combinatorial Mathematics: An Applied Introduction (Addison-Wesley, 2003), pp. 175–180. Also, one can find most integer sequences in the online encyclopedia of integer sequences: http://oeis.org

^[20]See D. Selva and E. Crawley, “Integrated Assessment of Packaging Architectures in Earth Observing Programs,” in Aerospace Conference, 2010 IEEE (Big Sky, MN: IEEE, 2010), pp. 3–12, for a discussion on monolithic versus distributed architectures for Earth observing satellites, including Envisat.

^[21] The interested reader can find more information about the Metop mission and the sensitive sounder in D. Blumstein, “IASI Instrument: Technical Overview and Measured Performances,” Proceedings of SPIE (Spie, 2004), p. 19.

^[22] See M. Chiang and M. Yang, M. “Towards Network X-ities from a Topological Point of View: ­Evolvability and Scalability,” 42nd Annual Allerton Conference on Communication, Control and Computing, 2004.

^[23] See N.S. Haverty, “MIL-STD 1553—A Standard for Data Communications,” Communication and Broadcasting 10 (1985): 29–33.

^[24] See N.C. Strole, “The IBM Token-Ring Network—A Functional Overview.” Network, IEEE 1.1 (1987): 23–30.

^[25] See K.W. Matthee et al., “Bringing Internet Connectivity to Rural Zambia Using a Collaborative ­Approach,”. International Conference on Information and Communication Technologies and Development, 2007. ICTD 2007 (IEEE, 2007).

^[26] For a more exhaustive methods-based text, see G. Parnell, P. Driscoll, and D. Henderson (Eds.), ­Decision Making in Systems Engineering and Management (Wiley, 2011) or D.M. Buede, The ­Engineering Design of Systems: Models and Methods (Wiley, 2009).

^[27] Typical combinatorial optimization algorithms include branch and bound, cutting planes, approximation algorithms, network optimization algorithms, and dynamic programming, among others. Several texts contain exhaustive introductions to these techniques. See, for example, A. Schrijver, Combinatorial Optimization (Springer, 2002), p. 1800, or D. Bertsimas and R. Weismantel, Optimization over Integers (Belmont, MA: Dynamic Ideas, 2005).

^[28] See, for example, K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation 6, no. 2 (2002): 182–197. doi:10.1109/4235.996017

^[29] For an introduction to these other techniques from design of experiments, see F. Pukelsheim, Optimal Design of Experiments (SIAM, 2006).

^[30] A good review of several meta-heuristics is given in F. Glover and G.A. Kochenberger, Handbook in Metaheuristics (New York: Kluwer Academic Publishers, 2003).

^[31]A more exhaustive discussion of heuristics and meta-heuristics is provided in F. Glover and G.A. ­Kochenberger, Handbook in Metaheuristics (New York: Kluwer Academic Publishers, 2003). It ­includes a discussion of hyper-heuristics—that is, heuristics used to choose between heuristics.

^[32]See J.H. Holland, Adaptation in Natural and Artificial Systems, 2nd ed. (Cambridge, MA: MIT Press, 1992).

^[33]See, for example, D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley Professional, 1989) or K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation 6, no. 2 (2002): 182–197.

^[34] Tabu search was first introduced by Fred Glover as a stand-alone meta-heuristic in F. Glover, “Tabu Search—Part I,” ORSA Journal on Computing 1, no. 3 (1989): 190–206 and F. Glover, “Tabu Search: Part II,” ORSA Journal on Computing 2, no. 1 (1990): 4–32. Its use within genetic algorithms has also been studied. See F. Glover, J.P. Kelly, and M. Laguna, “Genetic Algorithms and Tabu Search: Hybrids for Optimization,” Computers & Operations Research 22, no. 1 (1995): 111–134.

^[35] See an example in the context of the NEOSS problem in D. Selva, “Experiments in Knowledge-intensive System Architecting: Interactive Architecture Optimization.” In 2014 IEEE Aerospace ­Conference, Big Sky, Montana.

^[36] E. Burke, G. Kendall, J. Newall, and E. Hart, “Hyper-heuristics: An Emerging Direction in Modern Search Technology.” In Handbook of Metaheuristics, Springer US, pp. 457–474.