This paper proposes a modified iterated greedy(IG) algorithm to deal with FJSP problem in order to provide a simpler metaheuristic, which is easier to code and to reproduce than some other much more complex met
Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity Applied Soft Computing, 12 (2012), pp. 2896-2912 Google Scholar 25 Xiaofeng Li, Zhao Hai Greedy Algorithm Solution of Flexible Flow Shop Scheduling Problem IJCSNS International Journal of Computer Science ...
In this research, we propose a modified iterated greedy algorithm (MIG) to reduce the cost by consuming less CPU time. MIG provides a simple and easily applicable method that can compete with more complex meta-heuristics. The proposed algorithm MIG consists of two phases, each phase is derived...
Xu S, Li Y, Li Q (2024) A deep reinforcement learning method based on a transformer model for the flexible job shop scheduling problem. Electronics 13(18):3696. https://doi.org/10.3390/electronics13183696 Article MATH Google Scholar He J, Li J (2024) Deep reinforcement learning based on...
For the job-shop scheduling environment, Liu et al. [9] developed a multi-objective scheduling method for the classical job-shop scheduling problem (JSP) with total energy consumption and total weighted tardiness as objectives. The above review illustrates that current research has not sufficiently ...
applied to this optimal strategy. The efficiency has been improved after using the new representation, and also the objective values outperform others.1. Introduction The classical Job-shop Scheduling Problem (JSP) concerns determination of a set of jobs on a set of machines so that the makespan ...
The flexible job shop scheduling problem with parallel batch processing operation (FJSP_PBPO) in this study is motivated by real-world scenarios observed in electronic product testing workshops. This research aims to tackle the deficiency of effective me
and six state features are designed to improve the state feature representation by using two-way scheduling method,including four state features that distinguish the optimal action and two state features that are related to the learning goal.An extended variant of graph isomorphic network GIN++is ...
better choices are identified using lookahead, based on solutions obtained by repeatedly using a greedy heuristic. This paper first illustrates how the Pilot method improves upon some simple well known dispatch heuristics for the job-shop scheduling problem. The Pilot method is then shown to be a ...
All the metaheuristics are embedded in a Greedy Randomized Adaptive Search Procedure. The different versions of the archived GRASP approach are compared using large industrial instances. The numerical results show that the proposed approach provides good solutions regarding the preferences. Finally, the ...