A robust optimisation approach for the milk run problem with time windows with inventory uncertainty: an auto industry supply chain case study

In this paper, we introduce a robust optimisation approach to solve the milk run system with time window with inventory uncertainty. This approach yields routes that minimise transportation costs while satisfying all inventory in a given bounded uncertainty set. The idea of the milk run problem has been used in the context of logistic and supply chain problems in order to manage the transportation of materials. Since the resulted problem formulation is NP-hard, and in order to solve the underlying problem, a novel algorithm entitled robust optimisation has been proposed. We apply the model to solve some numerical examples to show robust solution efficiency versus deterministic. Since the resulted problem illustrates that grows up time in this method is progressive, and in order to solve the large-scale problems, particle swarm optimisation has been proposed. We also observe that the robust solution amounts to a clever management of the remaining vehicle capacity compared to uniformly and non-uniformly distributing this slack over the vehicles.

[1]  L El Ghaoui,et al.  ROBUST SOLUTIONS TO LEAST-SQUARE PROBLEMS TO UNCERTAIN DATA MATRICES , 1997 .

[2]  J. K. Lenstra,et al.  Complexity of vehicle routing and scheduling problems , 1981, Networks.

[3]  Xiao-Feng Xie,et al.  Adaptive particle swarm optimization on individual level , 2002, 6th International Conference on Signal Processing, 2002..

[4]  Brian Kallehauge,et al.  Formulations and exact algorithms for the vehicle routing problem with time windows , 2008, Comput. Oper. Res..

[5]  Paolo Toth,et al.  Branch-And-Bound Algorithms for the Capacitated VRP , 2002, The Vehicle Routing Problem.

[6]  George B. Dantzig,et al.  The Truck Dispatching Problem , 1959 .

[7]  Arkadi Nemirovski,et al.  Robust Convex Optimization , 1998, Math. Oper. Res..

[8]  Jun Zhang,et al.  Adaptive Particle Swarm Optimization , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[9]  Allen L. Soyster,et al.  Technical Note - Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming , 1973, Oper. Res..

[10]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[11]  Melvyn Sim,et al.  The Price of Robustness , 2004, Oper. Res..

[12]  Melvyn Sim,et al.  Robust discrete optimization and network flows , 2003, Math. Program..

[13]  Timon C. Du,et al.  A real-time vehicle-dispatching system for consolidating milk runs , 2007 .

[14]  Paolo Toth,et al.  Exact algorithms for the vehicle routing problem, based on spanning tree and shortest path relaxations , 1981, Math. Program..

[15]  Philippe Lacomme,et al.  A genetic algorithm for a bi-objective capacitated arc routing problem , 2006, Comput. Oper. Res..

[16]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[17]  Geraldo Robson Mateus,et al.  A genetic and set partitioning two-phase approach for the vehicle routing problem with time windows , 2007, Comput. Oper. Res..

[18]  Herman R. Leep,et al.  A vehicle routing problem solved by using a hybrid genetic algorithm , 2007, Comput. Ind. Eng..

[19]  Laurent El Ghaoui,et al.  Robust Solutions to Uncertain Semidefinite Programs , 1998, SIAM J. Optim..

[20]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[21]  F. Ordóñez,et al.  A robust optimization approach for the capacitated vehicle routing problem with demand uncertainty , 2008 .

[22]  A Ben Tal,et al.  ROBUST SOLUTIONS TO UNCERTAIN PROGRAMS , 1999 .

[23]  Donald Goldfarb,et al.  Robust convex quadratically constrained programs , 2003, Math. Program..