A Two-Stage Optimization Model for Staggered Work Hours

References

• Arnott, R., Rave, T., & Schöb, R. (2005). Staggered work hours for dominant employers. In Alleviating urban traffic congestion (pp. 135–185). Cambridge, MA: MIT Press.
   Google Scholar
• Ban, X.J., Ferris, M., & Liu, H.X. (2010). Numerical studies on reformulation techniques for continuous network design problems with asymmetric user equilibrium. International Journal of Operations Research and Information Systems, 1(1), 52–72.
   Google Scholar
• Ban, X.J., & Liu, H.X. (2009). A link-node discrete-time dynamic second best toll pricing model with a relaxation solution algorithm. Networks and Spatial Economics, 9(2), 243–267.
   Web of Science ®Google Scholar
• Ban, X.J., Liu, H.X., Ferris, M.C., & Ran, B. (2008). A link-node complementarity model and solution algorithm for dynamic user equilibria with exact flow propagations. Transportation Research Part B: Methodological, 42(9), 823–842.
   Web of Science ®Google Scholar
• Burkard, R., Pardalos, P., & Pitsoulis, L. (1998). The quadratic assignment problem. In P.M. Pardalos & D.-Z. Du (Eds.), Handbook of combinatorial optimization, (pp. 241–338). Dordrecht, The Netherlands: Kluwer Academic Publishers.
   Google Scholar
• Chu, X. (1995). Endogenous trip scheduling: The Henderson approach reformulated and compared with the Vickrey approach. Journal of Urban Economics, 37(3), 324–343.
   Web of Science ®Google Scholar
• Emmerink, R.H. M., & van Beek, P. (1997). Empirical analysis of work schedule flexibility: Implications for road pricing and driver. Urban Studies (Routledge), 34(2), 217–235.
   Web of Science ®Google Scholar
• Ferris, M.C., & Munson, T. (2000). Complementarity problems in gams and the path solver. Journal of Economic Dynamics and Control, 24(2), 165–188.
   Web of Science ®Google Scholar
• Gärling, T., Jakobsson, C., Loukopoulos, P., & Fujii, S. (2004). Adaptation of private car use in response to travel demand management measures: Potential roles of intelligent transportation systems. Journal of Intelligent Transportation Systems, 8(4), 189–194.
   Google Scholar
• Guiliano, G., & Golob, T.F. (1990). Staggered work hours for traffic management: A case study. Transportation Research Record, 1280, 46–58.
   Google Scholar
• Hahn, P.H., Kim, B.-J., Guignard, M., Smith, J., & Zhu Y.-R. (2008). An algorithm for the generalized quadratic assignment problem. Computational Optimization and Application, 40(3), 351–372.
   Web of Science ®Google Scholar
• Henderson, J.V. (1981). The economics of staggered work hours. Journal of Urban Economics, 9(3), 349–364.
   Web of Science ®Google Scholar
• Heydecker, B., & Verlander, N. (1999). Calculation of dynamic traffic equilibrium assignment. In Proceedings of the European transport conference (Vol Seminar F, pp. 79–91). London.
   Google Scholar
• Holguín-Veras, J., Ozbay, K., & Cerreño, A.D. (2005, March). Evaluation study of port Authority of New York and New Jersey's time of day pricing initiative. Technical report FHWA/NJ-2005-005, Federal Highway Administrations/U.S. Department of Transportation. Available at: http://www.state.nj.us/transportation/refdata/research/reports/FHWA-NJ-2005-005.pdf
   Google Scholar
• Holguín-Veras, J., Silas, M., Polimeni, J., & Cruz, B. (2007). An investigation on the effectiveness of joint receiver-carrier policies to increase truck traffic in the off-peak hours. Networks and Spatial Economics, 7(3), 277–295.
   Web of Science ®Google Scholar
• Holguín-Veras, J., Silas, M., Polimeni, J., Cruz, B. (2008). An investigation on the effectiveness of joint receiver-carrier policies to increase truck traffic in the off-peak hours. Networks and Spatial Economics, 8(4), 327–354.
   Web of Science ®Google Scholar
• Holguín-Veras, J., Wang, Q., Xu, N., & Ozbay, K. (2011). The impacts of time of day pricing on car user behavior: Findings from the Port Authority of New York and New Jersey's initiative. Transportation, 38, 427–443.
   Web of Science ®Google Scholar
• Holguín-Veras, J., Wang, Q., Xu, N., Ozbay, K., Cetin, M., & Polimeni, J. (2006). The impacts of time of day pricing on the behavior of freight carriers in a congested urban area: Implications to road pricing. Transportation Research Part A: Policy and Practice, 40(9), 744–766.
   Web of Science ®Google Scholar
• Jones, D.J., Nakamoro, T., & Cilliers, M. (1977). Implications for travel behavior and transport invesment policy: Implications for travel behavior and transport investment policy. Technical report, University of California, Berkeley, CA.
   Google Scholar
• Koopmans, T.C., & Beckman, M.J. (1957). Assignment problems and the location of economic activities. Econometrica, 25, 53–76.
   Web of Science ®Google Scholar
• Maric, D. (1977). Staggered working hours. In Adapting working hours to modern needs. Geneva, Switzerland International Labor Organization.
   Google Scholar
• Mun, S.-I., & Yonekawa, M. (2006). Flextime, traffic congestion and urban productivity. Journal of Transport Economics and Policy, 40(3), 329–358.
   Google Scholar
• O’Malley, B., & Selinger, C.S. (1973). Staggered work hours in manhattan. Traffic Engineering and Control, 14(9), 418–423.
   Google Scholar
• Owens, R.D., & Warmer, G.H. V. (1973). The effect of staggered working hours on traffic volumes at a large industrial complex. Traffic Engineering, 13(11), 61–64.
   Google Scholar
• Pisarski, A.E. (2006). Commuting in America III: The third national report on commuting patterns and trend. Technical report. Washington, DC, Transportation Research Board.
   Google Scholar
• Ran, B., & Boyce, D.E. (1996). Modeling dynamic transportation networks: An intelligent transportation systems oriented approach (2nd ed.). New York. NY: Springer-Verlag.
   Google Scholar
• Ran, B., Hall, R.W., & Boyce, D.E. (1996). A link-based variational inequality model for dynamic departure time/route choice. Transportation Research Part B: Methodological, 30(1), 31–46.
   Web of Science ®Google Scholar
• Sahni, S., & Gonzalez, T. (1976). P-complete approximation problems. Journal of the Association of Computing Machinery, 23, 555–565.
   Web of Science ®Google Scholar
• Silas, M.A. (2009). An investigation on off-hour delivery policy design using optimal incentives and a behavioral micro-simulation approach.Ph.D. thesis. Rensselaer Polytechnic Institute, Troy, NY.
   Google Scholar
• Szeto, W.Y., & Lo, H.K. (2005). The impact of advanced traveler information services on travel time and schedule delay costs. Journal of Intelligent Transportation Systems, 9(1), 47–55.
   Google Scholar
• Szeto, W.Y., & Lo, H.K. (2006). Dynamic traffic assignment: Properties and extensions. Transportmetrica, 2(1), 31–52.
   Web of Science ®Google Scholar
• Transportation Research Board. (1980, November). Alternative work schedules: Impacts on transportation. National cooperative highway research program; Synthesis of highway practice 73.
   Google Scholar
• Vickrey, W.S. (1969). Congestion theory and transport investment. American Economic Review, 59(2), 251–260.
   Web of Science ®Google Scholar
• Wardrop, J.G. (1952). Some theoretical aspects of road traffic research. Proceedings of the Institute of Civil Engineers Part II, 325–378.
   Google Scholar
• Wismans, L., Van Berkum, E., & Bliemer, M. (2011). Modelling externalities using dynamic traffic assignment models: A review. Transport Reviews, 31(4), 521–545.
   Web of Science ®Google Scholar
• Yushimito, W.F. (2011). Mitigating peak congestion with staggered work hours: Effects, models and implications.Ph.D. thesis. Rensselaer Polytechnic Institute, Troy, NY.
   Google Scholar
• Yushimito, W. F., Ban, X., & Holguín-Veras, J. (2013). Correcting the market failure in work trips with work rescheduling: an analysis using bi-level models for the firm-workers interplay. Networks and Spatial Economics, 1–33. In press. DOI: 10.1007/s11067-013-9213-7
   Google Scholar