Geodesic
A Heuristic Hybrid Framework for Vector Job Scheduling
Yugoslav journal of operations research, Tome 27 (2017) no. 1, p. 31 Cet article a éte moissonné depuis la source eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts

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We examine the first phase of a known NP-hard 2-stage assembly problem. It consists of sequencing a set of jobs having multiple components to be processed. Each job has to be worked on independently on a specific machine. We consider these jobs to form a vector of tasks. Our objective is to schedule jobs on the particular machines in order to minimize the completion time before the second stage starts. We first develop a new mathematical programming formulation of the problem and test it on a small problem instance using an integer programming solver. Then, we develop a heuristic algorithm based on Ant Colony Optimization and Variable Neighborhood Search metaheuristics in order to minimize the total completion time. The performance of our implementation appears to be effcient and effective.
Classification : 90B06, 90C05, 90C08
Keywords: Variable Neighborhood Search, Ant Colony Optimization, Scheduling, Integer Programming 
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     author = {Nareyus I Lawrance Amaldass and Cormac Lucas and Nenad Mladenovi\'c},
     title = {A {Heuristic} {Hybrid} {Framework} for {Vector} {Job} {Scheduling}},
     journal = {Yugoslav journal of operations research},
     pages = {31 },
     year = {2017},
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     number = {1},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_2017_27_1_a1/}
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Nareyus I Lawrance Amaldass; Cormac Lucas; Nenad Mladenović. A Heuristic Hybrid Framework for Vector Job Scheduling. Yugoslav journal of operations research, Tome 27 (2017) no. 1, p. 31 . http://geodesic.mathdoc.fr/item/YJOR_2017_27_1_a1/