Environmental effects in an integrated hub location and pricing problem

Document Type : Article


Department of Industrial Engineering, University of Bojnord, Bojnord, P.O. Box 94531-55111, Iran


The product pricing decision is one of the important factors in the profitability of organizations, which has a key role in their survival. Moreover, the pricing is determined based on the demand and location of applicants. Therefore, the location of facilities and services influence the pricing. Also, the location problem is a critical issue in the survival of the organization. Furthermore, the hub location problem is a type of location problems, which has many applications and saves time and money. On the other hand, location is impossible without considering transportation and transportation has many negative effects on environmental, such as greenhouse gas emissions, air pollution, noise, etc. Considering this reason, it is important to consider the environmental costs to reduce the adverse effects. In this paper, we consider integrated pricing and hub location problem with environmental costs in the competitive market that customer choice is calculated according to the logit model (LM). We use a genetic algorithm (GA) to solve and observe the environmental cost, entrant profit, incumbent income, the impact of customer sensitivity and discount between hubs on the entrant profit. As a final point, the computational experiments demonstrate that the suggested GA is both efficient and effective.


  • References

    • A. “Factors Influencing Pricing Decisions”, Int J Econ & Manag Sci, 5(1), pp. 312-315 (2016).
    • S, Monemi, R.N, Nickel, S, "Multi-period hub location problems in transportation", Transport Res E-Log, 75(1), pp.67-94 (2015).
    • Karimi, H, Setak, M, "A bi-objective incomplete hub location-routing problem with flow shipment scheduling", Appl Math Model, 57(1), pp. 406-431 (2018).
    • J, Sundarraj.R.P. “Hub location at Digital Equipment Corporation: A comprehensive analysis of qualitative and quantitative factors”, Eur J Oper Res, 137(2), pp. 336-347 (2002).
    • A. “CO2 Emissions from freight transport in the UK”, In Transport and Climate Change (Vol. 2). T. Reley, L. Chapman, Emerald Group Publishing Limited, New York (2007).
    • S, Shiyi.H. “Pricing for the clean air: Evidence from Chinese housing market”, J Clean Prod. 206(1), pp. 297-306 (2019).
    • T, Laporte.G. (2011). “The Pollution-Routing Problem”, Transport Res B-Meth, 45(8), pp. 1232-1250 (2011).
    • L.A. “Discrete Choice Modelling and Air Travel Demand: Theory and Applications (Vol. 5)”. UK: Georgia Institute of Technology, USA (2016).
    • Rayfield, W.Z, Rusmevichientong, P, Topaloglu, H. "Approximation methods for pricing problems under the nested logit model with price bounds", INFORMS J Comput, 27(2), 335-357 (2015).
    • Beckmann, M. J., Thisse, J. F. The location of production activities. In Handbook of regional and urban economics (Vol. 1, pp. 21-95). Elsevier (1987).
    • Goldman, A. “Optimal Location for Centers in a Network”. Transport Sci, 3(4), pp. 352-360 (1969).
    • O'Kelly.M.E. “The Location of Interacting Hub Facilities”, Transport Sci, 20(2), pp. 92-106 (1986).
    • J.F, Ernst, A.T, Krishnamoorthy.M. “Hub Arc Location Problems: Part I—Introduction and Results”, Manage Sci, 51(10), pp. 1540-1555 (2005).
    • J.F, Ernst, A.T, Krishnamoorthy.M. “Hub arc location Problems: Part II—formulations and optimal algorithms”, Manage Sci, 51(10), pp. 1556-1571 (2005).
    • J.F. “Hub location for time-definite transportation”, Comput Oper Res, 36(12), pp. 3107-3116 (2009).
    • S, Schöbel.A, Sonneborn.T. “Hub location problems in urban traffic networks”, In P. Niittymäki.J, Mathematics Methods and Optimization in Transportation Systems pp. 95-107, Kluwer Academic Publishers (2001).
    • S, Nickel.S. “Hub location problems in transportation networks”, Transport Res E-Log, 47(6), pp. 1092-1111 (2011).
    • N, Smilowitz.K. “Hub-and-spoke network alliances and mergers: Price-location competition in the airline industry”, Transport Res B-Meth, 41(4), pp. 394-409 (2007).
    • p, Peeters.D, Thisse.J. “Facility location under zone pricing”, J Regional Sci, 37(1), pp. 1-22 (1997).
    • C.Y.C, Lu.H. “The multi-store location and pricing decisions of a spatial monopoly”, Reg Sci Urban Econ, 28(3), pp. 255-281 (1998).
    • Zhang, Y, "Designing a retail store network with strategic pricing in a competitive environment", Int J Prod Econ, 159(1), pp. 265-273 (2015).
    • Lüer-Villagra. A & Marianov.V. “A competitive hub location and pricing problem”, Eur J Oper Res, 231(3), pp. 734-744 (2013).
    • M, Sadeghi-Dastaki.M, Karimi.H. “Investigating zone pricing in a location-routing problem using a variable neighborhood search algorithm”, Int J Eng, 28(11), pp. 1624-1633 (2015).
    • H, Setak. M. “ Proprietor and customer costs in the incomplete hub location-routing network topology”, Appl Math Model, 38(3), pp. 1011-1023 (2014).
    • E, Eydi. A, Nakhai. I. “Reliable Hierarchical Multimodal Hub Location Problem: Models and Lagrangian Relaxation Algorithm”, Scientia Iranica, DOI:10.24200/sci.2018.50797.1870.
    • J, Harback.K.T. “Pricing the major US hub airport”, J Urban Econ, 66(1), pp. 33-56 (2009).
    • P.T. “A note on pricing of hub and spoke networks”, Econ Lett, 30(2), pp. 165-169 (1989).
    • J.I. “Congestion Pricing and Capacity of Large Hub Airports : A Bottleneck Model with Stochastic Queues”, Econometrica, 63(2), pp. 327-370 (1995).
    • T, zhang.A, zhang.Y. “A note on optimal airport pricing in a hub-and-spoke system”, Transport Res B-Meth, 30(1), pp. 11-18 (1996).
    • G, Black.J. “Hub-and-Spoke Networks and the Inclusion of Environmental Costs on Airport Pricing”, Transport Res D-Trans Env, 3(5), pp. 275-296 (1998).
    • T.M. “Airfare pricing determinants in hub-to-hub markets”, J Transp Geogr, 14(1), pp. 15-22 (2006).
    • O’Kelly, M. E. “Fuel burn and environmental implications of airline hub networks”. Transport Res D-Trans Env, 17(7), pp. 555-567 (2012).
    • Loo, B.P.Y, Linna L, Voula P, Ioanna P. "CO2 emissions associated with hubbing activities in air transport: an international comparison", J Transp Geogr, 34, 185-193 (2014).
    • Niakan, F., Vahdani, B., Mohammadi, M. “A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach” Eng Opt, 47(12), pp. 1670-1688 (2015).
    • Zhalechian, M., Tavakkoli-Moghaddam, R., Rahimi, Y., Jolai, F. “An interactive possibilistic programming approach for a multi-objective hub location problem: Economic and environmental design”. Soft. Comput, 52, pp.699-713 (2017).
    • S, Derudder.B, Witlox.F. “The impact of hub hierarchy and market competition on airfare pricing in US hub-to-hub markets”, J Air Transp Manag, 32(2),pp. 65-70 (2013).
    • M, Zhang.A. “Hub congestion pricing: Discriminatory passenger charges”, Econ of Transp, 5(1), pp. 37-48 (2016).
    • Lin, M.H, Zhang.Y. “Hub-airport congestion pricing and capacity investment”, Transport Res B-Meth, 101(1), pp. 89-106 (2017).
    • Cunha C.B, Silva. M.R, “A genetic algorithm for the problem of configuring a hub-and-spoke network for a LTL trucking company in Brazil,” J. Oper. Res., 179(3), pp. 747-758, (2007).
    • Topcuoglu, H., Corut, F., Ermis., M, Yilmaz, G., “Solving the uncapacitated hub location problem using genetic algorithms,” Oper. Res., 32(4), pp. 967-984, (2005).
    • Rudolph G, “Convergence analysis of canonical genetic algorithms,” IEEE Trans. Neural Networks, 5(1), pp. 96-101, (1994).
    • O'kelly, M. E. “A quadratic integer program for the location of interacting hub facilities”, Eur J Oper Res, 32(3), pp. 393-404 (1987).
    • H, Alumur.S, Kara.B, Karasan.O. “A tabu-search based heuristic for the hub covering problem over incomplete hub networks”, Comput Oper Res, 36(12), pp. 3088-3096 (2010).
    • Akçelik.R, Besley.M. “Operating cost, fuel consumption, and emission models in aaSIDRA and aaMOTION”, 25th Conference of Australian Institute of Transport research (2013).
    • G. “Motor vehicle dynamics : modeling and simulation” World Scientific, Italy (1997).