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Reinforcement Learning for Short-Term Production Scheduling with Sequence-Dependent Setup Waste
2020
ERCIM News
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In this case, along with the aforementioned constraints, the setup waste is heavily dependent on the production sequence. ...
new field "Neural Combinatorial Optimization" addressing combinatorial tasks [2]. ...
doi:10.18154/rwth-2020-11165
fatcat:x3xvomljjrd5xhplvj62i36hwi
Solving the Steel Continuous Casting Problem using an Artificial Intelligence Model
2021
International Journal of Advanced Computer Science and Applications
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The SCC problem is an important NP-hard combinatorial optimization problem and can be seen as three stages hybrid flowshop problem. ...
We have proposed to solve it a recurrent neural network (RNN) with LSTM cells that we will executed in the cloud. ...
the termination time of the last charge at the third stage with their inter-sequence dependent setup times. ...
doi:10.14569/ijacsa.2021.01212105
fatcat:l27fnxlh7bh2lkyplrz45lnfxe
Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption
2016
European Journal of Operational Research
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To cope with combinatorial complexity, we also develop a constructive heuristic for fast trade-off analysis between makespan and energy consumption. ...
We analyze the trade-off between minimizing makespan, a measure of service level and total energy consumption, an indicator for environmental sustainability of a two-machine sequence dependent permutation ...
For a given speed vector, the scheduling heuristic SDH constructs a near-optimal sequence with respect to C max . ...
doi:10.1016/j.ejor.2015.08.064
fatcat:vazfwavjnjd2rcztzplf535lmu
Production smoothing in just-in-time manufacturing systems: a review of the models and solution approaches
2007
International Journal of Production Research
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Production smoothing is one of the most important tactical planning activities for the efficient operation of mixed-product just-in-time (JIT) manufacturing systems. ...
Although a relatively recent line of work considers alternative manufacturing environments, an incomplete understanding of the practical and modelling challenges associated with production smoothing hinders ...
McMullen (2002) introduces the concept of production smoothing for manufacturing systems where the final stage of manufacturing operations is a flow shop with sequence-dependent setup times for the end-products ...
doi:10.1080/00207540701223410
fatcat:fwsqtexhxfbslecav4kp42q7li
A state of art review on optimization techniques in just in time
2014
Uncertain Supply Chain Management
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The introductory section deals with the philosophy of JIT, and the concept involved in Kanban optimization and later this paper reviews literature on optimization Technique in JIT implementation. ...
As a manufacturing company has to become competitive for its survival, it has to supply products of consistent high quality at reliable and reduced delivery time. ...
In a batch production system, the switching over from one product to other product depends on many factors such as stock reaching to the threshold level, different priority schemes, economical setups, ...
doi:10.5267/j.uscm.2013.10.006
fatcat:ybqarfueabfoflidleqptmk5by
Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons
2000
IEEE Transactions on Evolutionary Computation
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This paper examines recent developments in the field of evolutionary computation for manufacturing optimization. ...
The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most manufacturing optimization problems are combinatorial and NP hard. ...
ACKNOWLEDGMENT The authors would like to thank the reviewers for their helpful comments. ...
doi:10.1109/4235.850651
fatcat:akevaqtprzab5cgs3y3y534aju
A Three-Stage Optimization Algorithm for the Stochastic Parallel Machine Scheduling Problem with Adjustable Production Rates
2013
Discrete Dynamics in Nature and Society
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We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. ...
Therefore, the decision variables include both the production schedule (sequences of jobs) and the production rate of each machine. ...
In fact, PSO-SA can be used for almost any stochastic combinatorial optimization problem. Therefore, PSO-SA can provide a baseline for comparison with our algorithm. ...
doi:10.1155/2013/280560
fatcat:ecxvfpaplzdztjsbh5hfsgd5q4
Algorithm architectures to support large-scale process systems engineering applications involving combinatorics, uncertainty, and risk management
2002
Computers and Chemical Engineering
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These architectures are then embedded into a simulation-based optimization (SIMOPT) architecture to address both combinatorial character and significant data uncertainty. ...
In particular, highly customized mathematical programming architectures are discussed for time-based problems involving significant combinatorial character. ...
For example, effectively setting the proper pricing or timing of a consumer product promotion can depend on manufacturing operations (e.g. inventory levels, changeover costs, waste, etc.) and a competitor's ...
doi:10.1016/s0098-1354(01)00744-x
fatcat:uv3dq575dvey7lgmvcozzsh4se
Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art
2010
Journal of Environmental Management
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Finally, we conclude by summarizing the evolution of ECMPRO over the past decade together with the avenues for future research. ...
Gungor and Gupta [1999, Issues in environmentally conscious manufacturing and product recovery: a survey. ...
Brander and Forsberg (2005) develop a cyclic lot scheduling heuristic for disassembly processes by considering sequence-dependent setups. ...
doi:10.1016/j.jenvman.2009.09.037
pmid:19853369
fatcat:2c7cc2wowjaahdemy2rnz7gana
Key performance indicators for sustainable manufacturing evaluation in automotive companies
2011
2011 IEEE International Conference on Industrial Engineering and Engineering Management
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Assembly Line Balancing Problem with Bounded Processing Times, Learning Effect, and Sequence-dependent Setup Times Nima HAMTA, Seyyed Mohammad Taghi FATEMI GHOMI, M. ...
, Florian GEIGER 347 A Worker Assignment for Machine Cluster in the Manufacturing Cell Suksan PROMBANPONG, Waraporn SEENPIPAT Optimal Production Policy of Production System with Inventory-level-dependent ...
doi:10.1109/ieem.2011.6118084
dblp:conf/ieem/AmrinaY11
fatcat:donp6m7jijfylo4xgfngxccfru
Learning from the past to shape the future: a comprehensive text mining analysis of OR/MS reviews
2020
Omega : The International Journal of Management Science
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Furthermore, a text mining analysis of the papers citing OR/MS literature reviews showed that optimization continues to be one of the most highly influential methodological contributions of OR/MS to other ...
areas and that topics such as circular economy, carbon emissions, and social commerce have yet to find some traction in OR/MS research, suggesting future research and multidisciplinary opportunities for ...
of
research
46
5344
setup times, scheduling problems, flowshop scheduling, parallel machines, flow
shop, survey scheduling, single machine, job shop, setup cost, classification scheme
8
Combinatorial ...
doi:10.1016/j.omega.2020.102388
fatcat:fi6nuthsbncn3dxzijukyonpwu
A single-machine scheduling problem with multiple unavailability constraints: A mathematical model and an enhanced variable neighborhood search approach
2017
Journal of Computational Design and Engineering
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This research focuses on a scheduling problem with multiple unavailability periods and distinct due dates. The objective is to minimize the sum of maximum earliness and tardiness of jobs. ...
In order to optimize the problem exactly a mathematical model is proposed. ...
Wang [34] proposed a bi-objective optimization model for the problem of production scheduling and preventive maintenance in a single-machine context with sequence-dependent setup times, while during ...
doi:10.1016/j.jcde.2016.08.001
fatcat:qzzsqb4tl5egncrc2ddr3pqmoe
Grasp: An Annotated Bibliography
[chapter]
2002
Operations Research/Computer Science Interfaces Series
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A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. ...
GRASP has been applied to a wide range of combinatorial optimization problems, ranging from scheduling and routing to drawing and turbine balancing. ...
McGahan.A GRASP for single machine scheduling with sequence dependent setup costs and linear delay penalties.Computers & Operations Research, 23:881-895, 1996.A GRASP for single machine scheduling with ...
doi:10.1007/978-1-4615-1507-4_15
fatcat:kvaokik4m5a2bezgzzcfaqjbui
Understanding and Optimizing Packed Neural Network Training for Hyper-Parameter Tuning
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2002.02885v3 fatcat:r6qam74ekjfrvggvbjvdavgzfeOther Versions
The results suggest: (1) packing two models can bring up to 40% performance improvement over unpacked setups for a single training step and the improvement increases when packing more models; (2) the benefit ...
when training multiple neural network models on limited resources; (4) a pack-aware Hyperband is up to 2.7x faster than the original Hyperband, with this improvement growing as memory size increases and ...
In contrast, an isolated sharing way (e.g., training models isolatedly in sequence) may lead to duplicated work and wasted resources. ...
arXiv:2002.02885v4
fatcat:bzrbaltbzzfnvbsrelouhqkxoq
Spatiotemporal Planning of Construction Projects: A Literature Review and Assessment of the State of the Art
2020
Frontiers in Built Environment
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Their objectives are to increase collaboration, ensure smooth flows of information, improve productivity, reduce different types of waste, and stabilize production. ...
Traditional scheduling methods based on activities modeling have become less adapted to this new reality. ...
Yeh (1995) formulated the problem of construction site layout as a combinatorial optimization problem by using the annealed neural network model and the Hopfield neuronal network. ...
doi:10.3389/fbuil.2020.00128
fatcat:p7a5dctpvvfw3agkgtnidam3sm
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