Hybrid metaheuristic techniques for optimising sugarcane rail operations

Mixed integer programming and parallel-machine job shop scheduling are used to solve the sugarcane rail transport scheduling problem. Constructive heuristics and metaheuristics were developed to produce a more efficient scheduling system and so reduce operating costs. The solutions were tested on small and large size problems. High-quality solutions and improved CPU time are the result of developing new hybrid techniques which consist of different ways of integrating simulated annealing and Tabu search techniques.

[1]  Dario Pacciarelli,et al.  Job-shop scheduling with blocking and no-wait constraints , 2002, Eur. J. Oper. Res..

[2]  Erhan Kozan,et al.  Scheduling trains as a blocking parallel-machine job shop scheduling problem , 2009, Comput. Oper. Res..

[3]  Kathryn A. Dowsland,et al.  Simulated Annealing , 1989, Encyclopedia of GIS.

[4]  Erhan Kozan,et al.  A disjunctive graph model and framework for constructing new train schedules , 2010, Eur. J. Oper. Res..

[5]  Peter Rossmanith,et al.  Simulated Annealing , 2008, Taschenbuch der Algorithmen.

[6]  Dario Pacciarelli,et al.  A branch and bound algorithm for scheduling trains in a railway network , 2007, Eur. J. Oper. Res..

[7]  Erhan Kozan,et al.  A job-shop scheduling approach for optimising sugarcane rail operations , 2011 .

[8]  Chompoonoot Kasemset,et al.  Bi-level multi-objective mathematical model for job-shop scheduling: the application of Theory of Constraints , 2010 .

[9]  Erhan Kozan,et al.  Machine Scheduling techniques to optimise sugarcane rail transport systems , 2009 .

[10]  Xuesong Zhou,et al.  Single-Track Train Timetabling with Guaranteed Optimality: Branch-and-Bound Algorithms with Enhanced Lower Bounds , 2007 .

[11]  Ceyda Oguz,et al.  Parallel machine scheduling with flexible resources , 2012, Comput. Ind. Eng..

[12]  E. S. Karapidakis,et al.  Hybrid Simulated Annealing–Tabu Search Method for Optimal Sizing of Autonomous Power Systems With Renewables , 2012, IEEE Transactions on Sustainable Energy.

[13]  Wanneng Shu.  Quantum-Inspired Genetic Algorithm Based on Simulated Annealing for Combinatorial Optimization Problem , 2009 .

[14]  De-fu Zhang,et al.  An effective hybrid algorithm for the problem of packing circles into a larger containing circle , 2005, Comput. Oper. Res..

[15]  Mitsuo Gen,et al.  Evolutionary Techniques for Automation , 2009, Handbook of Automation.

[16]  Andrew Higgins,et al.  A simulation model for capacity planning in sugarcane transport , 2005 .

[17]  Mostafa Zandieh,et al.  Bi-objective partial flexible job shop scheduling problem: NSGA-II, NRGA, MOGA and PAES approaches , 2012 .

[18]  S. Zolfaghari,et al.  Jointly solving the group scheduling and machining speed selection problems: A hybrid tabu search and simulated annealing approach , 1999 .

[19]  Shokri Z. Selim,et al.  Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem , 1999 .

[20]  Shimon Y. Nof,et al.  Springer Handbook of Automation , 2009, Handbook of Automation.

[21]  Ceyda Oguz,et al.  Hybrid flow-shop scheduling problems with multiprocessor task systems , 2004, Eur. J. Oper. Res..

[22]  P. G. Everitt,et al.  Cane transport scheduling : an integrated system , 1999 .

[23]  V. Cerný.  Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm , 1985 .

[24]  Éric D. Taillard,et al.  Parallel Taboo Search Techniques for the Job Shop Scheduling Problem , 1994, INFORMS J. Comput..

[25]  Manoj Kumar Tiwari,et al.  Modeling machine loading problem of FMSs and its solution methodology using a hybrid tabu search and , 2004 .

[26]  Graham Kendall,et al.  A Classification of Hyper-heuristic Approaches , 2010 .

[27]  Shih-Wei Lin,et al.  Applying a hybrid simulated annealing and tabu search approach to non-permutation flowshop scheduling problems , 2009 .

[28]  Erhan Kozan,et al.  A sequencing approach for creating new train timetables , 2010, OR Spectr..

[29]  Mitsuo Gen,et al.  Advanced scheduling problem using constraint programming techniques in SCM environment , 2002 .

[30]  Graham Kendall,et al.  Hyper-Heuristics: An Emerging Direction in Modern Search Technology , 2003, Handbook of Metaheuristics.

[31]  Miguel A. Salido,et al.  Mathematical Solutions for Solving Periodic Railway Transportation , 2009 .

[32]  Joaquin Rodriguez,et al.  A constraint programming model for real-time train scheduling at junctions , 2007 .