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   Solving A New Multi-Objective Unrelated Parallel Machines Scheduling Problem By Hybrid Teaching-Learning Based Optimization  
   
نویسنده Sadati A. ,Tavakkoli-Moghaddam R. ,Naderi B. ,Mohammadi M.
منبع International Journal Of Engineering - 2017 - دوره : 30 - شماره : 2 - صفحه:224 -233
چکیده    This paper considers a scheduling problem of a set of independent jobs on unrelated parallel machines (upms) that minimizes the maximum completion time (i.e., makespan or 𝐶𝑚𝑎𝑥), maximum earliness (𝐸𝑚𝑎𝑥), and maximum tardiness (𝑇𝑚𝑎𝑥) simultaneously. jobs have non-identical due dates, sequencedependent setup times and machine-dependent processing times. a multi-objective mixed-integer linear programming (milp) is considered and then solved with the ε-constraint method in small-sized problems. the results are compared with those obtained by meta-heuristic algorithms. furthermore, an effective hybrid multi-objective teaching–learning based optimization (hmotlbo) algorithm is proposed, whose performance is compared with a non-dominated sorting genetic algorithm (nsga-ii) for test problems generated at random. the results show that the proposed hmotlbo outperforms the nsga-ii in terms of different metrics.
کلیدواژه Teaching–Learning Based Optimization ,Unrelated Parallel Machines ,Makespantardiness ,Earliness
آدرس Islamic Azad University, Science And Research Branch, Department Of Industrial Engineering, ایران, Islamic Azad University, South Tehran Brach, School Of Industrial Engineering, ایران, Kharazmi University, Faculty Of Engineering, Department Of Industrial Engineering, ایران, Kharazmi University, Faculty Of Engineering, Department Of Industrial Engineering, ایران
 
     
   
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