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Reinforcement Learning for Short-Term Production Scheduling with Sequence-Dependent Setup Waste

Vladimir Samsonov, Mohamed Behery, Gerhard Lakemeyer
2020 ERCIM News  
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

Achraf BERRAJAA
2021 International Journal of Advanced Computer Science and Applications  
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

S. Afshin Mansouri, Emel Aktas, Umut Besikci
2016 European Journal of Operational Research  
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

Mesut Yavuz, Elif Akçali
2007 International Journal of Production Research  
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

Ineen Sultana, Imtiaz Ahmed
2014 Uncertain Supply Chain Management  
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

C. Dimopoulos, A.M.S. Zalzala
2000 IEEE Transactions on Evolutionary Computation  
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

Rui Zhang
2013 Discrete Dynamics in Nature and Society  
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

Joseph F. Pekny
2002 Computers and Chemical Engineering  
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

Mehmet Ali Ilgin, Surendra M. Gupta
2010 Journal of Environmental Management  
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

E. Amrina, S. M. Yusof
2011 2011 IEEE International Conference on Industrial Engineering and Engineering Management  
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

Rodrigo Romero-Silva, Sander de Leeuw
2020 Omega : The International Journal of Management Science  
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

Maziar Yazdani, Seyed Mohammad Khalili, Mahla Babagolzadeh, Fariborz Jolai
2017 Journal of Computational Design and Engineering  
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]

Paola Festa, Mauricio G.C. Resende
2002 Operations Research/Computer Science Interfaces Series  
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]

Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
2021 arXiv   pre-print
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

Fabian Ardila, Adel Francis
2020 Frontiers in Built Environment  
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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