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A populated local search with differential evolution for blocking flowshop scheduling problem
(2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015)
This paper presents a populated local search algorithm through a differential evolution algorithm for solving the blocking flowshop scheduling problem under makespan criterion. Iterated greedy and iterated local search ...
A differential evolution algorithm with variable neighborhood search for multidimensional knapsack problem
(2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015)
This paper presents a differential evolution algorithm with a variable neighborhood search to solve the multidimensional knapsack problem. Unlike the studies employing check and repair operators, we employ some sophisticated ...
An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time
(International Journal of Production Research, 2015)
This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) ...
An iterated greedy algorithm for the hybrid flowshop problem with makespan criterion
(IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIPLS 2014: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, Proceedings, 2014)
The main contribution of this paper is to present some novel constructive heuristics for the the hybrid flowshop scheduling (HFS) problem with the objective of minimizing the makespan for the first time in the literature. ...
A general variable neighborhood search algorithm for the no-idle permutation flowshop scheduling problem
(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013)
In this study, a general variable neighborhood search (GVNS) is presented to solve no-idle permutation flowshop scheduling problem (NIPFS), where idle times are not allowed on machines. GVNS is a metaheuristic, where inner ...
Metaheuristic algorithms for the quadratic assignment problem
(Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems, CIPLS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, 2013)
This paper presents two meta-heuristic algorithms to solve the quadratic assignment problem. The iterated greedy algorithm has two main components, which are destruction and construction procedures. The algorithm starts ...
Lagrangian heuristic for scheduling a steelmaking-continuous casting process
(Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Scheduling, CISched 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, 2013)
One of the biggest bottlenecks in iron and steel production is the steelmaking-continuous casting (SCC) process, which consists of steel-making, refining and continuous casting. The production scheduling of SCC is a complex ...
A variable iterated greedy algorithm with differential evolution for the no-idle permutation flowshop scheduling problem
(Computers and Operations Research, 2013)
This paper presents a variable iterated greedy algorithm (IG) with differential evolution (vIG-DE), designed to solve the no-idle permutation flowshop scheduling problem. In an IG algorithm, size d of jobs are removed from ...
A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion
(Applied Mathematical Modelling, 2013)
In this paper, we present a discrete artificial bee colony algorithm to solve the no-idle permutation flowshop scheduling problem with the total tardiness criterion. The no-idle permutation flowshop problem is a variant ...
A variable iterated greedy algorithm with differential evolution for solving no-idle flowshops
(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012)
In this paper, we present a variable iterated greedy algorithm where its parameters (basically destruction size and probability of whether or not to apply the iterated greedy algorithm to an individual) are optimized by ...
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