Soft Computing Methods in Transport and Logistics

The current economic context generates in supply chain management greater demands for flexibility and dynamism. In addition, there is an increase in uncertainty that adds more complexity to the problems associated with planning and management. Soft Computing offers a set of methodologies capable of responding to these challenges. This work provides an overview of transport and logistics problems, as well as the most representative combinatorial optimization models. Specifically, it focuses on the treatment of uncertainty through fuzzy optimization and metaheuristics methodologies. Promising results from the use of this approach suggest emerging areas of application, which are presented and described.

[1]  Sharon M. Ordoobadi.  Development of a supplier selection model using fuzzy logic , 2009 .

[2]  Yu-Jun Zheng,et al.  Bio-Inspired Meta-Heuristics for Emergency Transportation Problems , 2014, Algorithms.

[3]  Dragan Pamučar,et al.  Transport spatial model for the definition of green routes for city logistics centers , 2016 .

[4]  Yong Liu,et al.  Vehicle routing problem based on a fuzzy customer clustering approach for logistics network optimization , 2015, J. Intell. Fuzzy Syst..

[5]  Natalija Jolić,et al.  Intelligent Transportation System and Night Delivery Schemes for City Logistics , 2011 .

[6]  Talbi El-Ghazali,et al.  Optimization algorithms for multi-objective problems with fuzzy data , 2014, 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM).

[7]  R. J. Kuo,et al.  Solving CVRP with time window, fuzzy travel time and demand via a hybrid ant colony optimization and genetic algortihm , 2012, 2012 IEEE Congress on Evolutionary Computation.

[8]  Patrick Siarry,et al.  A survey on optimization metaheuristics , 2013, Inf. Sci..

[9]  Xiaolei Ma,et al.  Location optimization of multiple distribution centers under fuzzy environment , 2012, Journal of Zhejiang University SCIENCE A.

[10]  Pietro Romano,et al.  Supply chain management: an analytical framework for critical literature review , 2000 .

[11]  Daniele Vigo,et al.  Vehicle Routing Problems with Profits , 2014, Vehicle Routing.

[12]  Julio Brito,et al.  TRANSPORT ROUTE PLANNING MODELS BASED ON FUZZY APPROACH , 2012 .

[13]  M. Pal,et al.  THE P-CENTER PROBLEM ON FUZZY NETWORKS AND REDUCTION OF COST , 2008 .

[14]  Benita M. Beamon,et al.  Facility location in humanitarian relief , 2008 .

[15]  Luk N. Van Wassenhove,et al.  Humanitarian aid logistics: supply chain management in high gear , 2006, J. Oper. Res. Soc..

[16]  José A. Moreno-Pérez,et al.  Fuzzy Optimization in Vehicle Routing Problems , 2009, IFSA/EUSFLAT Conf..

[17]  Bo K. Wong,et al.  A survey of the application of fuzzy set theory in production and operations management: 1998-2009 , 2011 .

[18]  A. Gunasekaran,et al.  Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications , 2007 .

[19]  Alain Hertz,et al.  The capacitated team orienteering and profitable tour problems , 2007, J. Oper. Res. Soc..

[20]  Raul Poler Escoto,et al.  Fuzzy optimization for supply chain planning under supply, demand and process uncertainties , 2009, Fuzzy Sets Syst..

[21]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[22]  Jesús González-Feliu,et al.  Vehicle routing problems for city logistics , 2017, EURO J. Transp. Logist..

[23]  Francisco Saldanha-da-Gama,et al.  Facility location and supply chain management - A review , 2009, Eur. J. Oper. Res..

[24]  Lawrence W. Lan,et al.  A NOVEL MODEL FOR QUICK RESPONSE TO DISASTER RELIEF DISTRIBUTION , 2005 .

[25]  Zhong-Zhong Jiang,et al.  A credibility-based fuzzy location model with Hurwicz criteria for the design of distribution systems in B2C e-commerce , 2010, Comput. Ind. Eng..

[26]  José A. Moreno-Pérez,et al.  Solving the Team Orienteering Problem with fuzzy scores and constraints , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[27]  F. Herrera,et al.  EUROPEAN JOURNAL OF OPERATIONAL , 1992 .

[28]  Yang Peng,et al.  A Particle Swarm Optimization to Vehicle Routing Problem with Fuzzy Demands , 2010, J. Convergence Inf. Technol..

[29]  Francisco Herrera,et al.  A Walk into Metaheuristics for Engineering Optimization: Principles, Methods and Recent Trends , 2015, Int. J. Comput. Intell. Syst..

[30]  Shaoren Wang,et al.  Fuzzy location-routing problem for emergency logistics systems , 2014 .

[31]  Xin Shen,et al.  An emergency logistics transportation path optimization model by using trapezoidal fuzzy , 2014, 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD).

[32]  Konrad Lewczuk,et al.  Vehicle Routing In An Urban Area:Environmental And Technological Determinants , 2013 .

[33]  Christian Prins,et al.  A survey of recent research on location-routing problems , 2014, Eur. J. Oper. Res..

[34]  Angel A. Juan,et al.  A simulation-based algorithm for the integrated location and routing problem in urban logistics , 2013, 2013 Winter Simulations Conference (WSC).

[35]  Ziyou Gao,et al.  A green train scheduling model and fuzzy multi-objective optimization algorithm , 2013 .

[36]  Abdul Razak Salleh,et al.  On normalistic vague soft groups and normalistic vague soft group homomorphism , 2015 .

[37]  Morikazu Nakamura,et al.  A Fuzzy Optimal Routing Problem for Sightseeing , 2005 .

[38]  Armand Baboli,et al.  Sustainable Inventory Routing Problem for Perishable Products by Considering Reverse Logistic , 2016 .

[39]  Shuzhu Zhang,et al.  Swarm intelligence applied in green logistics: A literature review , 2015, Eng. Appl. Artif. Intell..

[40]  Erel Avineri.  Soft Computing Applications in Traffic and Transport Systems: A Review , 2005 .

[41]  Alain Hertz,et al.  Metaheuristics for the team orienteering problem , 2005, J. Heuristics.

[42]  Dirk Van Oudheusden,et al.  The Mobile Tourist Guide: An OR Opportunity , 2007, OR Insight.

[43]  Sanjay Silakari,et al.  Survey of Metaheuristic Algorithms for Combinatorial Optimization , 2012 .

[44]  José A. Moreno-Pérez,et al.  Fuzzy location problems on networks , 2004, Fuzzy Sets Syst..

[45]  Jan Fabian Ehmke,et al.  Integration of Information and Optimization Models for Routing in City Logistics , 2012, International series in operations research and management science.

[46]  K. Ganesh,et al.  Models for Practical Routing Problems in Logistics , 2014 .

[47]  Charalampos Konstantopoulos,et al.  Heuristics for the time dependent team orienteering problem: Application to tourist route planning , 2015, Comput. Oper. Res..

[48]  Xiao Hong,et al.  B2C E-commerce Vehicle Delivery Model and Simulation , 2013 .

[49]  Lixin Tang,et al.  Iterated local search algorithm based on very large-scale neighborhood for prize-collecting vehicle routing problem , 2006 .

[50]  Gilbert Laporte,et al.  The impact of depot location, fleet composition and routing on emissions in city logistics , 2016 .

[51]  Jian Xu,et al.  Genetic algorithm for the vehicle routing problem with time windows and fuzzy demand , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[52]  Jiuh-Biing Sheu,et al.  Challenges of emergency logistics management , 2007 .

[53]  Jan Fabian Ehmke,et al.  Advanced routing for city logistics service providers based on time-dependent travel times , 2012, J. Comput. Sci..

[54]  Maghsoud Amiri,et al.  Application of a hybrid simulated annealing-mutation operator to solve fuzzy capacitated location-routing problem , 2013 .

[55]  José L. Verdegay,et al.  Fuzzy Models and Resolution Methods for Covering Location Problems: an Annotated Bibliography , 2016, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[56]  Ferani E. Zulvia,et al.  Application of a fuzzy ant colony system to solve the dynamic vehicle routing problem with uncertain service time , 2016 .

[57]  Sai Ho Chung,et al.  Survey of Green Vehicle Routing Problem: Past and future trends , 2014, Expert Syst. Appl..

[58]  Yoshinori Suzuki,et al.  A new truck-routing approach for reducing fuel consumption and pollutants emission , 2011 .

[59]  Emrah Demir,et al.  Robust solutions to the pollution-routing problem with demand and travel time uncertainty , 2017 .

[60]  T. Tsiligirides,et al.  Heuristic Methods Applied to Orienteering , 1984 .

[61]  Michal Koháni,et al.  Very large street routing problem with mixed transportation mode , 2011, Central Eur. J. Oper. Res..

[62]  F. Maffioli,et al.  On prize-collecting tours and the asymmetric travelling salesman problem , 1995 .

[63]  Johan Woxenius,et al.  Localisation of freight consolidation centres serving small road hauliers in a wider urban area: barriers for more efficient freight deliveries in Gothenburg , 2014 .

[64]  Eiichi Taniguchi,et al.  Modelling Effects of E-Commerce on Urban Freight Transport , 2004 .

[65]  Jie Chen,et al.  Vehicle Routing Problem with Fuzzy Demands and the Particle Swarm Optimization Solution , 2010, 2010 International Conference on Management and Service Science.

[66]  Michael Drexl,et al.  A survey of variants and extensions of the location-routing problem , 2015, Eur. J. Oper. Res..

[67]  Mehdi Ghazanfari,et al.  A hybrid simulated annealing based heuristic for solving the location-routing problem with fuzzy demands , 2013 .

[68]  David Simchi-Levi,et al.  The logic of logistics , 1997 .

[69]  Michael Browne,et al.  Home Delivery and the Impacts on Urban Freight Transport: A Review , 2014 .

[70]  Jiuh-Biing Sheu,et al.  An emergency logistics distribution approach for quick response to urgent relief demand in disasters , 2007 .

[71]  Mark S. Daskin,et al.  Strategic facility location: A review , 1998, Eur. J. Oper. Res..

[72]  Maria Grazia Speranza,et al.  Optimal solutions for routing problems with profits , 2013, Discret. Appl. Math..

[73]  M. Vila,et al.  A general model for fuzzy linear programming , 1989 .

[74]  D. Lambert,et al.  SUPPLY CHAIN MANAGEMENT -- MORE THAN A NEW NAME FOR LOGISTICS , 1997 .

[75]  Tomohiro Murata,et al.  Particle swarm optimization for vehicle routing problem with uncertain demand , 2013, 2013 IEEE 4th International Conference on Software Engineering and Service Science.

[76]  Richard F. Hartl,et al.  Heuristics for the multi-period orienteering problem with multiple time windows , 2010, Comput. Oper. Res..

[77]  Kenneth Sörensen,et al.  Metaheuristics - the metaphor exposed , 2015, Int. Trans. Oper. Res..

[78]  Dario Pacciarelli,et al.  The value of real-time traffic information in urban freight distribution , 2018, J. Intell. Transp. Syst..

[79]  Eiichi Taniguchi,et al.  CITY LOGISTICS. NETWORK MODELLING AND INTELLIGENT TRANSPORT SYSTEMS , 2001 .

[80]  M. Carmen Garrido,et al.  Soft-computing based heuristics for location on networks: The p-median problem , 2011, Appl. Soft Comput..

[81]  El-Ghazali Talbi,et al.  Using multiobjective metaheuristics to solve VRP with uncertain demands , 2010, IEEE Congress on Evolutionary Computation.

[82]  Ashutosh Tiwari,et al.  A review of soft computing applications in supply chain management , 2010, Appl. Soft Comput..

[83]  Kwai-Sang Chin,et al.  A decision support system for optimizing dynamic courier routing operations , 2014, Expert Syst. Appl..

[84]  Yahia Zare Mehrjerdi,et al.  Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands , 2013, Eur. J. Oper. Res..

[85]  F. Russo,et al.  A classification of city logistics measures and connected impacts , 2010 .

[86]  Carlos Eduardo Carrillo Mendez.  Team Orienteering Problem with Time Windows and Fuzzy Scores , 2016 .

[87]  Carlos Cruz Corona,et al.  Solving the Truck and Trailer Routing Problem with Fuzzy Constraints , 2015, Int. J. Comput. Intell. Syst..

[88]  Shaligram Pokharel,et al.  Optimization models in emergency logistics: A literature review , 2012 .

[89]  Piero P. Bonissone,et al.  On heuristics as a fundamental constituent of soft computing , 2008, Fuzzy Sets Syst..