An iterated greedy algorithm for solving the total tardiness parallel blocking flow shop scheduling problem

Ribas, Imma; Companys, Ramón; Tort‐Martorell, Xavier

doi:10.1016/j.eswa.2018.12.039

Cited by 89 publications

(21 citation statements)

References 38 publications

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“…However, Li et al 19 used hybrid ABC algorithm to solve the problem of parallel batch distributed flowshop with deteriorating jobs. Many algorithms have been proposed for solving the DPFSP, such as tabu search (TS) algorithm, 20 genetic algorithm (GA), 21 simulated annealing (SA) algorithm, 22 and iterated greedy (IG) algorithm 23 –28 solved a casting scheduling problem by a new coevolutionary artificial bee colony that proposed by Pan (P-ABC). Li et al 29 used a multi-objective algorithm to solve the problem of batch mixed flowshop with variable sub-batches.…”

Section: Introductionmentioning

confidence: 99%

Solving robotic distributed flowshop problem using an improved iterated greedy algorithm

Gao

et al. 2019

International Journal of Advanced Robotic Systems

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In this study, we propose an improved iterated greedy algorithm for solving the distributed permutation flowshop problem, where there is a single robot in each factory and the makespan needs to be minimized. In the problem considered, the robot is used to transfer each job from the predecessor machine to the successor machine. A blocking constraint between machines is considered, thus jobs should remain on the completed machine while waiting for the robot. The loading and unloading times are considered and different for all of the jobs conducted by the robot, and the deteriorating time is also considered. In the proposed algorithm, first, four types of neighborhood structures are developed. Then, the simulated annealing algorithm is embedded in the proposed algorithm to enhance the exploration abilities. Furthermore, a problem-specific destruction and construction strategies are investigated. Finally, several realistic instances were generated to test the proposed algorithm, and its competitive performance was verified based on detailed experimental comparisons.

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Section: Introductionmentioning

confidence: 99%

Solving robotic distributed flowshop problem using an improved iterated greedy algorithm

Gao

et al. 2019

International Journal of Advanced Robotic Systems

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“…Their results show the advantage of using their proposal over other methods, and even they claim that their method could work in a real-world application. Ribas et al [ 24 ] also use a greedy algorithm with a variable neighborhood search to a job-shop scheduling which has a constraint that increases the complexity of the problem by allowing a machine has a storage capability, so a machine can be not available before the previous machine has finished their job. They use two strategies to tackle this problem and to select the critical line which has the highest tardiness.…”

Section: State-of-the-artmentioning

confidence: 99%

Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic

Olivas

Amaya

Ortíz-Bayliss

et al. 2021

Computational Intelligence and Neuroscience

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Hyperheuristics rise as powerful techniques that get good results in less computational time than exact methods like dynamic programming or branch and bound. These exact methods promise the global best solution, but with a high computational time. In this matter, hyperheuristics do not promise the global best solution, but they promise a good solution in a lot less computational time. On the contrary, fuzzy logic provides the tools to model complex problems in a more natural way. With this in mind, this paper proposes a fuzzy hyperheuristic approach, which is a combination of a fuzzy inference system with a selection hyperheuristic. The fuzzy system needs the optimization of its fuzzy rules due to the lack of expert knowledge; indeed, traditional hyperheuristics also need an optimization of their rules. The fuzzy rules are optimized by genetic algorithms, and for the rules of the traditional methods, we use particle swarm optimization. The genetic algorithm will also reduce the number of fuzzy rules, in order to find the best minimal fuzzy rules, whereas traditional methods already use very few rules. Experimental results show the advantage of using our approach instead of a traditional selection hyperheuristic in 3200 instances of the 0/1 knapsack problem.

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“…On the other hand, the distributed flow shop scheduling problem has been recently solved by Ruiz et al (2019) by the IG method. Other objective apart from the total completion time like the total tardiness were considered by Ribas et al (2019) for the blocking flowshop problem. In this work also the IG was used for the resolution.…”

Section: Proposed Iterated Greedy Proceduresmentioning

confidence: 99%

An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

Missaoui

Boujelbène

2021

RAIRO-Oper. Res.

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Nowadays many industry consider an interval time as a due date instead of precise points in time. In this study, the hybrid flow shop scheduling problem with basic blocking constraint is tackled. Where jobs, if done within a due window, are deemed on time. Therefore, the criterion is to minimize the sum of weighted earliness and tardiness. This variant of the hybrid flowshop problem is not investigated to the best of our knowledge. we introduced a new metaheuristic centered on the iterated greedy approach. to evaluate the proposed method we start by the re-implementation and the comparison of seven well-selected procedures that treat the hybrid flowshop problem. In order to prove the robustness of our method, we evaluated it using a new benchmark of more than 1000 instances. The experimental results demonstrated that the proposed algorithm is effective and produces a very high solution.

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An iterated greedy algorithm for solving the total tardiness parallel blocking flow shop scheduling problem

Cited by 89 publications

References 38 publications

Solving robotic distributed flowshop problem using an improved iterated greedy algorithm

Solving robotic distributed flowshop problem using an improved iterated greedy algorithm

Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic

An effective iterated greedy algorithm for blocking hybrid flow shop problem with due date window

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