Simulated annealing with restart strategy for the blood pickup routing problem

This study develops a simulated annealing heuristic with restart strategy (SA_RS) for solving the blood pickup routing problem (BPRP). BPRP minimizes the total length of the routes for blood bag collection between a blood bank and a set of donation sites, each associated with a time window constraint that must be observed. The proposed SA_RS is implemented in C++ and tested on benchmark instances of the vehicle routing problem with time windows to verify its performance. The algorithm is then tested on some newly generated BPRP instances and the results are compared with those obtained by CPLEX. Experimental results show that the proposed SA_RS heuristic effectively solves BPRP.

[1]  Lidija Zadnik Stirn,et al.  A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food , 2008 .

[2]  Shih-Wei Lin,et al.  A simulated annealing heuristic for the team orienteering problem with time windows , 2012, Eur. J. Oper. Res..

[3]  Masoud Rabbani,et al.  Vehicle Routing with Time Windows and Customer Selection for Perishable Goods , 2015 .

[4]  Vincent F. Yu,et al.  Simulated annealing for the blood pickup routing problem , 2016 .

[5]  Attahiru Sule Alfa,et al.  A 3-OPT based simulated annealing algorithm for vehicle routing problems , 1991 .

[6]  Corina Pop Sitar,et al.  Heuristic Algorithms for Solving the Generalized Vehicle Routing Problem , 2011, Int. J. Comput. Commun. Control.

[7]  Jeroen Belien,et al.  Supply chain management of blood products: A literature review , 2012 .

[8]  P. D. Cumming,et al.  A Collections Planning Model for Regional Blood Suppliers: Description and Validation , 1976 .

[9]  George C. Runger,et al.  Using Experimental Design to Find Effective Parameter Settings for Heuristics , 2001, J. Heuristics.

[10]  Young Dae Ko,et al.  A vehicle routing problem of both refrigerated- and general-type vehicles for perishable food products delivery , 2016 .

[11]  Shuo-Yan Chou,et al.  Solving the truck and trailer routing problem based on a simulated annealing heuristic , 2009, Comput. Oper. Res..

[12]  Zne-Jung Lee,et al.  Applying Simulated Annealing Approach for Capacitated Vehicle Routing Problems , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[13]  Jinxin Yi Vehicle Routing with Time Windows and Time-Dependent Rewards: A Problem from the American Red Cross , 2003, Manuf. Serv. Oper. Manag..

[14]  Masoud Rabbani,et al.  Vehicle routing problem with considering multi-middle depots for perishable food delivery , 2016 .

[15]  Ching-Jung Ting,et al.  A simulated annealing heuristic for the capacitated location routing problem , 2010, Comput. Ind. Eng..

[16]  Yiyo Kuo,et al.  Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem , 2010, Comput. Ind. Eng..

[17]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[18]  Richard F. Hartl,et al.  Exact and heuristic algorithms for the vehicle routing problem with multiple interdependent time windows , 2008, Comput. Oper. Res..

[19]  Alex Van Breedam,et al.  Improvement heuristics for the Vehicle Routing Problem based on simulated annealing , 1995 .

[20]  Jeroen Beliën,et al.  Supply chain management of blood products: A literature review , 2012, Eur. J. Oper. Res..

[21]  Shih-Wei Lin,et al.  A simulated annealing heuristic for the multiconstraint team orienteering problem with multiple time windows , 2015, Appl. Soft Comput..

[22]  Wen-Chen Lee,et al.  An Intelligent System for Improving Performance of Blood Donation , 2011 .

[23]  Yuchun Xu,et al.  Development of a fuel consumption optimization model for the capacitated vehicle routing problem , 2012, Comput. Oper. Res..

[24]  Manus Rabinowitz,et al.  Policies for Reducing Blood Wastage in Hospital Blood Banks , 1977 .

[25]  Chung-Cheng Lu,et al.  A simulated annealing heuristic for the truck and trailer routing problem with time windows , 2011, Expert Syst. Appl..