A multiple colonies artificial bee colony algorithm for a capacitated vehicle routing problem and re-routing strategies under time-dependent traffic congestion

Abstract An Online Vehicle Routing Problem is a formation of Capacitated Vehicle Routing Problem with re-routing strategy to resolve the problem of inefficient vehicle routing caused by traffic congestion. A flexible delivery rerouting strategy is proposed, which aims at reducing the risk of late delivery. The method of terminating an exploration in a solution by the original ABC algorithm, when the solution is trapped in local optima, is to abandon the solution after specific tolerance limits are set. The phenomenon of local optimal traps will be repeated rapidly after a lengthy recursive process and will eventually result in a low quality solution, with a more complex combinatorial problem when the capability of the exploration is restricted by an inflexible termination criterion. Therefore, this paper proposes a novel scheme using a Multiple Colonies Artificial Bee Colony algorithm. The designs of the outstanding bee selection for colony communication show it to be superior in exploitation. The performance of the proposed algorithm is examined through by Capacitated Vehicle Routing instances and a case study, and the results indicate the potential of using real time information for data-driven vehicle scheduling.

[1]  Xiaorong Chen,et al.  Research on moving object detection based on improved mixture Gaussian model , 2015 .

[2]  Efrén Mezura-Montes,et al.  Elitist Artificial Bee Colony for constrained real-parameter optimization , 2010, IEEE Congress on Evolutionary Computation.

[3]  Jan Fabian Ehmke,et al.  Ensuring service levels in routing problems with time windows and stochastic travel times , 2015, Eur. J. Oper. Res..

[4]  Shengxiang Yang,et al.  Genetic Algorithms with Memory- and Elitism-Based Immigrants in Dynamic Environments , 2008, Evolutionary Computation.

[5]  Michael A. Haughton ROUTE REOPTIMIZATION'S IMPACT ON DELIVERY EFFICIENCY , 2002 .

[6]  John Wang Management Innovations for Intelligent Supply Chains , 2012 .

[7]  Shengxiang Yang,et al.  Ant colony optimization with memory-based immigrants for the dynamic vehicle routing problem , 2012, 2012 IEEE Congress on Evolutionary Computation.

[8]  Yuren Zhou,et al.  A dynamic multi-colony artificial bee colony algorithm for multi-objective optimization , 2015, Appl. Soft Comput..

[9]  Edward Cutrell,et al.  Accurate speed and density measurement for road traffic in India , 2013, ACM DEV '13.

[10]  Denis Borenstein,et al.  Real-time vehicle rerouting problems with time windows , 2009, Eur. J. Oper. Res..

[11]  Michel Gendreau,et al.  A review of dynamic vehicle routing problems , 2013, Eur. J. Oper. Res..

[12]  Barrie M. Baker,et al.  A genetic algorithm for the vehicle routing problem , 2003, Comput. Oper. Res..

[13]  Chelsea C. White,et al.  Optimal vehicle routing with real-time traffic information , 2005, IEEE Transactions on Intelligent Transportation Systems.

[14]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[15]  Roberto Montemanni,et al.  A multiple ant colony system for a vehicle routing problem with time windows and uncertain travel times , 2014 .

[16]  Michel Gendreau,et al.  A priori optimization with recourse for the vehicle routing problem with hard time windows and stochastic service times , 2014, Eur. J. Oper. Res..

[17]  Amir Ahmadi-Javid,et al.  A location-routing problem with disruption risk , 2013 .

[18]  Yannis Marinakis,et al.  improved particle swarm optimization algorithm for the apacitated location routing problem and for the location routing roblem with stochastic demands , 2015 .

[19]  Shengxiang Yang,et al.  Elitism-based immigrants for ant colony optimization in dynamic environments: Adapting the replacement rate , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[20]  Yuren Zhou,et al.  An elitism based multi-objective artificial bee colony algorithm , 2015, Eur. J. Oper. Res..

[21]  Ashita S. Bhagade,et al.  Artificial Bee Colony ( ABC ) Algorithm for Vehicle Routing Optimization Problem , 2012 .

[22]  André de Palma,et al.  Does providing information to drivers reduce traffic congestion , 1991 .

[23]  Michel Gendreau,et al.  A Tabu Search Heuristic for the Vehicle Routing Problem with Stochastic Demands and Customers , 1996, Oper. Res..

[24]  Philippe Augerat,et al.  Approche polyèdrale du problème de tournées de véhicules. (Polyhedral approach of the vehicle routing problem) , 1995 .

[25]  Richard F. Hartl,et al.  A survey on dynamic and stochastic vehicle routing problems , 2016 .

[26]  W. Y. Szeto,et al.  An artificial bee colony algorithm for the capacitated vehicle routing problem , 2011, Eur. J. Oper. Res..

[27]  Paolo Toth,et al.  Vehicle Routing , 2014, Vehicle Routing.

[28]  George M. Giaglis,et al.  Minimizing logistics risk through real‐time vehicle routing and mobile technologies: Research to date and future trends , 2004 .

[29]  C. Waters Vehicle-scheduling Problems with Uncertainty and Omitted Customers , 1989 .

[30]  Shengxiang Yang,et al.  Ant algorithms with immigrants schemes for the dynamic vehicle routing problem , 2015, Inf. Sci..

[31]  Pei Chun Lin,et al.  A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty , 2010 .

[32]  Dar-Shyang Lee,et al.  Effective Gaussian mixture learning for video background subtraction , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[34]  Shangyao Yan,et al.  The planning and real-time adjustment of courier routing and scheduling under stochastic travel times and demands , 2013 .

[35]  Mei-Shiang Chang,et al.  The real-time time-dependent vehicle routing problem , 2006 .

[36]  S. Thomas McCormick,et al.  Integer Programming and Combinatorial Optimization , 1996, Lecture Notes in Computer Science.

[37]  W. Art Chaovalitwongse,et al.  Scatter search for the stochastic travel-time vehicle routing problem with simultaneous pick-ups and deliveries , 2012, Comput. Oper. Res..

[38]  Patrick R. McMullen,et al.  Ant colony optimization techniques for the vehicle routing problem , 2004, Adv. Eng. Informatics.

[39]  Martha C. Wilson,et al.  The impact of transportation disruptions on supply chain performance , 2007 .

[40]  W. H. Ip,et al.  Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem , 2014 .

[41]  Gilbert Laporte,et al.  A Tabu Search Heuristic for the Vehicle Routing Problem , 1991 .

[42]  J.G.A.J. van der Vorst Management in logistics networks and nodes: concepts, technology and applications, edited by T. Blecker, W. Kersten and C. Gertz , 2010 .

[43]  Voratas Kachitvichyanukul,et al.  A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery , 2009, Comput. Oper. Res..

[44]  Gilbert Laporte,et al.  An Exact Algorithm for the Vehicle Routing Problem with Stochastic Demands and Customers , 1995, Transp. Sci..

[45]  Michael A. Haughton,et al.  Assigning delivery routes to drivers under variable customer demands , 2007 .

[46]  Denis Borenstein,et al.  A Lagrangian Heuristic for the Real-Time Vehicle Rescheduling Problem , 2009 .

[47]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .