×

zbMATH — the first resource for mathematics

Bi-level multi-objective optimization model for last mile delivery using a discrete approach. (English) Zbl 1376.90057
Summary: To reduce traffic congestion as well as to improve workforce productivity, a bi-level multi-objective model is proposed for an urban logistics metropolis, in which there are two decision-makers, one is the center operator (leader) of an urban consolidation center at the upper level and the other is the logistics party (follower) who manages the delivery at the lower level. In this model, we suppose the supply side risk and the demand side risk exist simultaneously and the decision-makers at both levels are risk-averse. The leader makes his decision by considering the demand from the follower and his own economic efficiency, environmental emissions, and highly dependent time windows with penalties for late delivery. The follower arranges his transportation plan by considering the cost for the order from retail stores and the time window set by the center operator at the upper level. To solve the resulting bi-level multi-objective model, a new solution method is constructed. Numerical tests are given to show the efficiency of our method.

MSC:
90C29 Multi-objective and goal programming
90C15 Stochastic programming
90C22 Semidefinite programming
90B06 Transportation, logistics and supply chain management
PDF BibTeX Cite
Full Text: DOI
References:
[1] DOI: 10.21042/AMNS.2016.1.00004 · Zbl 1423.68052
[2] DOI: 10.1287/trsc.1080.0235
[3] DOI: 10.1016/j.cie.2010.02.013
[4] Qu S.J., Bi-level optimization model for last mile retail cargo (2014)
[5] DOI: 10.1016/j.trb.2011.05.005
[6] DOI: 10.1108/09600031111175843
[7] DOI: 10.21042/AMNS.2016.1.00012 · Zbl 1423.68490
[8] DOI: 10.1007/978-1-4757-2836-1
[9] DOI: 10.1007/s10107-008-0259-0 · Zbl 1198.90347
[10] Farahi M.H., J. Math. Comput. Sci. 1 pp 313– (2010)
[11] Fukushima M., Ill-posed Variational Problems and Regularization Techniques pp 99– (2000)
[12] DOI: 10.1287/opre.1100.0910 · Zbl 1231.90303
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.