Last-mile distribution planning for fruit-and-vegetable cold chains

The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains.,The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residual shelf life, which changes with temperature, and is characterized by a stepped decrease during the transportation process as time goes on. A genetic algorithm (GA) is adapted to solve the problem because of its convincing ability to solve VRPTW-related problems. For this purpose, solution encoding, a fitness function and evolution operators are designed to deal with the complicated problem herein.,A distribution plan including required fleet size, vehicle routing sequence and what quality level should be shipped out to account for the quality degradation during vehicle transportation is generated. The results indicate that the fulfillment of various requirements of different customers for various fruits and vegetables and quality levels can be ensured with cost considerations.,This study presents a problem for last-mile delivery of fresh fruits and vegetables which considers multiple practical scenarios not studied previously. A solution algorithm based on a GA is developed to address this problem. The proposed model is easily applied to other types of perishable products.

[1]  Wenbin Hu,et al.  A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with Time Window , 2013, Entropy.

[2]  Anggara Hayun Anujuprana Shipping and Transport Optimization on Vehicle Routing Problem (VRP) with Genetic Algorithm , 2015 .

[3]  Henry C. W. Lau,et al.  Cost-optimization modelling for fresh food quality and transportation , 2016, Ind. Manag. Data Syst..

[4]  Fengming Tao,et al.  Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax , 2017 .

[5]  Moses Oginda,et al.  Effect of Recruitment and Selection of Employees on The Performance of Small and Medium Enterprises in Kisumu Municipality, Kenya , 2012 .

[6]  Ismail Uysal,et al.  Shelf life modelling for first-expired-first-out warehouse management , 2014, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  Mitsuo Gen,et al.  Network Models and Optimization: Multiobjective Genetic Algorithm Approach , 2008 .

[8]  Jagjit Singh Srai,et al.  Hierarchical modelling of Last Mile logistic distribution system , 2014 .

[9]  Brigitte Petersen,et al.  A predictive shelf life model as a tool for the improvement of quality management in pork and poultry chains , 2013 .

[10]  Qing Liu,et al.  Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions , 2016 .

[11]  X. D. Chen,et al.  An Optimization Model for the Vehicle Routing Problem in Multi-product Frozen Food Delivery , 2014 .

[12]  Yves Dallery,et al.  Ensuring supply chain safety through time temperature integrators , 2007 .

[13]  Sadiq M. Sait,et al.  Iterative computer algorithms with applications in engineering - solving combinatorial optimization problems , 2000 .

[14]  J. Kreyenschmidt,et al.  Determination of the shelf life of sliced cooked ham based on the growth of lactic acid bacteria in different steps of the chain , 2010, Journal of applied microbiology.

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

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

[17]  Samuel J. Raff,et al.  Routing and scheduling of vehicles and crews : The state of the art , 1983, Comput. Oper. Res..

[18]  Ahmed Saif,et al.  Cold supply chain design with environmental considerations: A simulation-optimization approach , 2016, Eur. J. Oper. Res..

[19]  J. Kuo,et al.  Developing an advanced Multi-Temperature Joint Distribution System for the food cold chain , 2010 .

[20]  Ching-Wu Chu,et al.  A heuristic algorithm for the truckload and less-than-truckload problem , 2005, Eur. J. Oper. Res..

[21]  Kristina Liljestrand,et al.  Capturing food logistics: a literature review and research agenda , 2015 .

[22]  Pisut Pongchairerks,et al.  A Genetic algorithm for a vehicle routing problem on a real application of Bakery delivery , 2010, 2010 2nd International Conference on Electronic Computer Technology.

[23]  Zhu Jinfeng,et al.  Cold Chain Logistics Distribution Network Planning Subjected to Cost Constraints , 2015 .

[24]  Philippe Lacomme,et al.  Order-first split-second methods for vehicle routing problems: A review , 2014 .

[25]  Guimei Zhang,et al.  Improving the structure of deep frozen and chilled food chain with tabu search procedure , 2003 .

[26]  Kenneth K. Boyer,et al.  THE LAST MILE CHALLENGE: EVALUATING THE EFFECTS OF CUSTOMER DENSITY AND DELIVERY WINDOW PATTERNS , 2009 .

[27]  André Langevin,et al.  An exact algorithm and a metaheuristic for the generalized vehicle routing problem with flexible fleet size , 2014, Comput. Oper. Res..

[28]  Paolo Toth,et al.  A hybrid Granular Tabu Search algorithm for the Multi-Depot Vehicle Routing Problem , 2014, J. Heuristics.

[29]  Chaug-Ing Hsu,et al.  A model for facilities planning for multi-temperature joint distribution system , 2011 .

[30]  T. A. Roberts,et al.  The effect of sodium chloride and temperature on the rate and extent of growth of Clostridium botulinum type A in pasteurized pork slurry. , 1987, The Journal of applied bacteriology.

[31]  Christos D. Tarantilis,et al.  Advanced vehicle routing algorithms for complex operations management problems , 2005 .

[32]  Gastón Ares,et al.  Sensory shelf-life estimation: A review of current methodological approaches , 2012 .

[33]  E. Voorde,et al.  Characteristics and Typology of Last-mile Logistics from an Innovation Perspective in an Urban Context , 2011 .

[34]  Mitsuo Gen,et al.  A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries , 2010, The 40th International Conference on Computers & Indutrial Engineering.

[35]  Heung-Suk Hwang,et al.  An improved model for vehicle routing problem with time constraint based on genetic algorithm , 2002 .

[36]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[37]  Burak Eksioglu,et al.  The vehicle routing problem: A taxonomic review , 2009, Comput. Ind. Eng..

[38]  Ismail Uysal,et al.  Time-Temperature Management Along the Food Cold Chain: A Review of Recent Developments. , 2017, Comprehensive reviews in food science and food safety.

[39]  G. La Scalia,et al.  An Innovative Shelf Life Model Based on Smart Logistic Unit for an Efficient Management of the Perishable Food Supply Chain , 2017 .

[40]  Hae-Soo Park,et al.  A genetic algorithm for the vendor-managed inventory routing problem with lost sales , 2016, Expert Syst. Appl..

[41]  Zou Yifeng,et al.  Application of Cold Chain Logistics Safety Reliability in Fresh Food Distribution Optimization , 2013 .

[42]  Loo Hay Lee,et al.  Heuristic methods for vehicle routing problem with time windows , 2001, Artif. Intell. Eng..

[43]  Pedro Amorim,et al.  The impact of food perishability issues in the vehicle routing problem , 2014, Comput. Ind. Eng..

[44]  L. Bodin ROUTING AND SCHEDULING OF VEHICLES AND CREWS–THE STATE OF THE ART , 1983 .

[45]  Chaug-Ing Hsu,et al.  Optimizing fleet size and delivery scheduling for multi-temperature food distribution , 2014 .

[46]  Brian Kallehauge,et al.  The Vehicle Routing Problem with Time Windows , 2006, Vehicle Routing.

[47]  Lone Gram,et al.  Food spoilage--interactions between food spoilage bacteria. , 2002, International journal of food microbiology.

[48]  Andrew Greasley,et al.  Improving “last mile” delivery performance to retailers in hub and spoke distribution systems , 2012 .

[49]  Chung-Cheng Lu,et al.  Data envelopment analysis for evaluating the efficiency of genetic algorithms on solving the vehicle routing problem with soft time windows , 2012, Comput. Ind. Eng..

[50]  R. Akkerman,et al.  An optimization approach for managing fresh food quality throughout the supply chain , 2011 .

[51]  Moncer Hariga,et al.  Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation , 2017 .

[52]  Mario Enea,et al.  A webGIS-based system for real time shelf life prediction , 2016, Comput. Electron. Agric..

[53]  Hui-Chieh Li,et al.  Vehicle routing problem with time-windows for perishable food delivery , 2007 .

[54]  Xiaolan Xie,et al.  Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care , 2013, Eur. J. Oper. Res..

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

[56]  Salama A. Mostafa,et al.  Using Genetic Algorithm in implementing Capacitated Vehicle Routing Problem , 2012, 2012 International Conference on Computer & Information Science (ICCIS).

[57]  Mei-Shiang Chang,et al.  Production scheduling and vehicle routing with time windows for perishable food products , 2009, Comput. Oper. Res..

[58]  Emmanouil E. Zachariadis,et al.  The load-dependent vehicle routing problem and its pick-up and delivery extension , 2015 .