Relevant bibliographies by topics / Job Shop Scheduling Problem (JSSP)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Job Shop Scheduling Problem (JSSP)'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Job Shop Scheduling Problem (JSSP)"

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APRIANA, I. WAYAN RADIKA, NI KETUT TARI TASTRAWATI, and KARTIKA SARI. "IMPLEMENTASI ALGORITMA CAT SWARM OPTIMIZATION DALAM MENYELESAIKAN JOB SHOP SCHEDULING PROBLEM (JSSP)." E-Jurnal Matematika 5, no. 3 (2016): 90. http://dx.doi.org/10.24843/mtk.2016.v05.i03.p126.

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Cat Swarm Optimization (CSO) algorithm is a metaheuristic algorithm which is based on two behaviors of cat, seeking and tracing. CSO algorithm is used in solving optimization problems. One of the optimization problems which can be seen in daily life is Job Shop Scheduling Problem (JSSP). This study aimed to observe the performance of CSO algorithm in solving JSSP. This study focused on 5 job-12 machine cases. According to this study, CSO algorithm was effective in solving real case of JSSP in 5 jobs – 12 machines scheduling at CV Mitra Niaga Indonesia agriculture tools industry. In implementin
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Fuentes-Penna, Alejandro, Lilibeth C. Gómez-Espinosa, and Alejandro Pérez Pasten Borja. "Introduction to Job Shop Scheduling to Model the Timetabling Scheduling Problem." International Journal of Combinatorial Optimization Problems and Informatics 13, no. 3 (2022): 63–74. https://doi.org/10.61467/2007.1558.2022.v13i3.310.

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The Timetabling Scheduling Problem (TTSP) is proposed as a schedule of a sequence of events between actors (teachers, students, workers, etc.) in a predefined period (typically hours), satisfying a set of constraints. TTSP has been traditionally considered in the operational research field and recently has been tackled with different Artificial Intelligence techniques. The proposed solutions to TTSP are in the range of traditional techniques (linear programming, whole programming, manual solution, network flow, etc.) and metaheuristic methods (simulations of human way, graph colouring, tabu se
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Xu, Long, and Wen Bin Hu. "The Effect of Crossover and Mutation Operators on Genetic Algorithm for Job Shop Scheduling Problem." Advanced Materials Research 542-543 (June 2012): 1251–59. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1251.

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Job Shop Scheduling Problem (JSSP) is a famous NP-hard problem in scheduling field. The concentration of JSSP is to find a feasible scheduling plan to figure out the earliest completion time under machine and processing sequence constraints. At present, genetic algorithm has been widely adopted in varies of operation research problems including JSSP, and good performance have been achieved. However, few work have stress the selection of varies operators when implemented for JSSP. Using benchmark problems, this paper compares the effect of crossover and mutation operators on genetic algorithm f
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Assafra, Khadija, Bechir Alaya, Salah Zidi, and Mounir Zrigui. "Optimization of transport constraints and quality of service for joint resolution of uncertain scheduling and the job-shop problem with routing (JSSPR) as opposed to the job-shop problem with transport (JSSPT)." Journal of Project Management 9, no. 2 (2024): 109–30. http://dx.doi.org/10.5267/j.jpm.2024.1.002.

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To better meet the qualitative and quantitative requirements of customers or relevant sector managers, workshop environments are implementing increasingly complex task management systems. The job shop scheduling problem (JSSP) involves assigning each task to a single machine while scheduling many tasks on different machines. Finding the best scheduling for machines is one of the challenging optimizations of difficult non-deterministic polynomial (NP) time problems. The fundamental goal of optimization is to shorten the makespan (total execution time of all tasks). This paper is interested in t
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Witkowski, Tadeusz. "Particle swarm optimization and discrete artificial bee colony algorithms for solving production scheduling problems." Technical Sciences 1, no. 22 (2019): 61–74. http://dx.doi.org/10.31648/ts.4348.

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This paper shows the use of Discrete Artificial Bee Colony (DABC) and Particle Swarm Optimization (PSO) algorithm for solving the job shop scheduling problem (JSSP) with the objective of minimizing makespan. The Job Shop Scheduling Problem is one of the most difficult problems, as it is classified as an NP-complete one. Stochastic search techniques such as swarm and evolutionary algorithms are used to find a good solution. Our objective is to evaluate the efficiency of DABC and PSO swarm algorithms on many tests of JSSP problems. DABC and PSO algorithms have been developed for solving real pro
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Maqsood, Shahid, M. Khurshid Khan, Alastair Wood, and I. Hussain. "A Novel Heuristic Rule for Job Shop Scheduling." International Journal of Customer Relationship Marketing and Management 4, no. 1 (2013): 28–40. http://dx.doi.org/10.4018/jcrmm.2013010103.

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Scheduling systems based on traditional heuristic rules, which deal with the complexities of manufacturing systems, have been used by researchers for the past six decades. These heuristics rules prioritise all jobs that are waiting to be processed on a resource. In this paper, a novel Index Based Heuristic (IBH) solution for the Job Shop Scheduling Problem (JSSP) is presented with the objective of minimising the overall Makespan (Cmax). The JSSP is still a challenge to researchers and is far from being completely solved due to its combinatorial nature. JSSP suits the challenges of current manu
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Nwozo, C. R., and S. O. Adewoye. "On Optimum Sequencing of Job Shop Scheduling in Manufacturing Shop." Data Science: Journal of Computing and Applied Informatics 7, no. 2 (2023): 96–102. http://dx.doi.org/10.32734/jocai.v7.i2-14375.

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Joh shop scheduling problem (JSSP) is an NP Hard problem. The most obvious real-world application of the JSSP is within manufacturing and machining as the parameter description describes. Companies that are able to optimize their machining schedules are able to reduce production time and cost in order to maximize profits. The aim of the problem is to find the optimum schedule for allocating shared resources over time to complete all n jobs within the problem. In this research we employ probability sequencing and make of comparison of job-shop sequencing rule such as first-come, first-served (F
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Liaqait, Raja Awais, Shermeen Hamid, Salman Sagheer Warsi, and Azfar Khalid. "A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0." Sustainability 13, no. 14 (2021): 7684. http://dx.doi.org/10.3390/su13147684.

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Scheduling plays a pivotal role in the competitiveness of a job shop facility. The traditional job shop scheduling problem (JSSP) is centralized or semi-distributed. With the advent of Industry 4.0, there has been a paradigm shift in the manufacturing industry from traditional scheduling to smart distributed scheduling (SDS). The implementation of Industry 4.0 results in increased flexibility, high product quality, short lead times, and customized production. Smart/intelligent manufacturing is an integral part of Industry 4.0. The intelligent manufacturing approach converts renewable and nonre
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Mehmood, Nasir, Muhammad Umer, and Ahmad Riaz. "A Survey of Recent Developments for JSSP and FJSSP Using ACO." Advanced Materials Research 816-817 (September 2013): 1133–39. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.1133.

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Ant Colony Optimization (ACO) is based on swarm intelligence and it is a constructive meta-heuristic which was first presented in 1991. Job Shop Scheduling Problem (JSSP) is very important problem of the manufacturing industry. JSSP is a combinatorial optimization problem which is NP-hard. The exact solution of NP-hard problem is very difficult to find. Therefore heuristics approach is the best approach for such problems. This paper shall overview the application of ant colony optimization on JSSP and Flexible Job Shop Scheduling problems (FJSSP). This paper shalll cover the major areas in whi
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Freud, David, and Amir Elalouf. "A Memetic Algorithm Approach for the Job-Shop Scheduling Problem with Variable Machine Efficiency and Maintenance Activities." Applied Sciences 15, no. 3 (2025): 1431. https://doi.org/10.3390/app15031431.

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Variable machine efficiency (VME) and maintenance activities (MA) are critical factors often unexplored in job scheduling problems. This paper introduces a new problem termed the job-shop scheduling problem with variable machine efficiency and maintenance activities (JSSP-VME-MT), wherein, unlike the traditional JSSP, machine efficiency and maintenance activities are explicitly incorporated into the scheduling process. The study proposes a novel memetic algorithm (MA) underpinned by a variable neighborhood descent (VND) local search strategy to address this complex problem. This methodology de
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Dissertations / Theses on the topic "Job Shop Scheduling Problem (JSSP)"

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Maqsood, Shahid. "The scheduling of manufacturing systems using Artificial Intelligence (AI) techniques in order to find optimal/near-optimal solutions." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/6322.

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This thesis aims to review and analyze the scheduling problem in general and Job Shop Scheduling Problem (JSSP) in particular and the solution techniques applied to these problems. The JSSP is the most general and popular hard combinational optimization problem in manufacturing systems. For the past sixty years, an enormous amount of research has been carried out to solve these problems. The literature review showed the inherent shortcomings of solutions to scheduling problems. This has directed researchers to develop hybrid approaches, as no single technique for scheduling has yet been succes
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Branquinho, Vasco Moreira da Fonseca. "Escalonamento da produção na SAPEC : consequências no seu desempenho." Master's thesis, Instituto Superior de Economia e Gestão, 2013. http://hdl.handle.net/10400.5/6586.

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Mestrado em Decisão Económica e Empresarial<br>No processo produtivo de uma indústria de fitofarmacêuticos deparamo-nos com problemas no sequenciamento e afetação de tarefas necessárias a encomendas. Este estudo destina-se à fábrica da maior multinacional portuguesa no ramo dos agro-químicos. A SAPEC Agro aposta numa estratégia vencedora no negócio agrícola e, neste ramo, a competição não é entre empresas, mas sim entre as cadeias de abastecimento. Com o crescimento da empresa e a sua internacionalização, inserida num ambiente altamente competitivo, torna-se fundamental automatizar o processo
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Wein, Lawrence M., and Philippe B. Chevalier. "A Broader View of the Job-Shop Scheduling Problem." Massachusetts Institute of Technology, Operations Research Center, 1989. http://hdl.handle.net/1721.1/5389.

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We define a job-shop scheduling problem with three dynamic decisions: assigning duedates to exogenously arriving jobs, releasing jobs from a backlog to the shop floor, and sequencing jobs at each workstation in the shop. The objective is to minimize both the work-in-process (WIP) inventory on the shop floor and the due-date lead time (due-date minus arrival date) of jobs, subject to an upper bound constraint on the proportion of tardy jobs. A general two-step approach to this problem is proposed: (1) release and sequence jobs in order to minimize the WIP inventory subject to completing jobs at
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Sousa, Sandra Isabel Ferreira de. "Heuristic approaches for a flexible job-shop scheduling problem." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/17578.

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Mestrado em Engenharia e Gestão Industrial<br>Este trabalho aborda um novo tipo de problema de escalonamento que pode ser encontrado em várias aplicações do mundo-real, principalmente na indústria transformadora. Em relação à configuração do shop floor, o problema pode ser classificado como flexible job-shop, onde os trabalhos podem ter diferentes rotas ao longo dos recursos e as suas operações têm um conjunto de recursos onde podem ser realizadas. Outras características de processamento abordadas são: datas possíveis de início, restrições de precedência (entre operações de um mesmo trabalho o
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Heitmann, Silvia. "Job-shop scheduling with limited buffer capacities." Doctoral thesis, Saarbrücken VDM Verlag Dr. Müller, 2007. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2007072013.

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In this work, we investigate job-shop problems where limited capacity buffers to store jobs in non-processing periods are present. In such a problem setting, after finishing processing on a machine, a job either directly has to be processed on the following machine or it has to be stored in a prespecified buffer. If the buffer is completely occupied the job may wait on its current machine but blocks this machine for other jobs. Besides a general buffer model,also specific configurations are considered.The key issue to develop fast heuristics for the job-shop problem with buffers is to find a c
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Al-Hinai, Nasr. "OPTIMIZING THE FLEXIBLE JOB-SHOP SCHEDULING PROBLEM USING HYBRIDIZED GENETIC ALGORITHMS." Flexible Services and Manufacturing Journal, 2011. http://hdl.handle.net/1993/4955.

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Flexible job-shop scheduling problem (FJSP) is a generalization of the classical job-shop scheduling problem (JSP). It takes shape when alternative production routing is allowed in the classical job-shop. However, production scheduling becomes very complex as the number of jobs, operations, parts and machines increases. Until recently, scheduling problems were studied assuming that all of the problem parameters are known beforehand. However, such assumption does not reflect the reality as accidents and unforeseen incidents happen in real manufacturing systems. Thus, an optimal schedule that is
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Cavalcante, Victor Fernandes. "Times assincronos para o job shop scheduling problem : heuristica de construção." [s.n.], 1995. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276030.

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Orientador: Pedro Sergio de Souza<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica<br>Made available in DSpace on 2018-07-20T09:57:07Z (GMT). No. of bitstreams: 1 Cavalcante_VictorFernandes_M.pdf: 2124078 bytes, checksum: 931a0a025284734a0bdaf335669442c5 (MD5) Previous issue date: 1995<br>Resumo: Times Assíncronos consistem numa nova técnica para solução aproximada de problemas que tem sido aplicada com sucesso a problemas de Otimização Combinatória. Esta técnica faz uso de diversos algoritmos heurísticos que cooperam
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Haddad, Elaine Gaspareto. "Times assincronos para o Job shop scheduling problem : heuristicas de melhoria." [s.n.], 1996. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276163.

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Orientadores: Pedro Sergio de Souza, Marcus Vinicius Poggi de Aragão<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-07-22T21:33:18Z (GMT). No. of bitstreams: 1 Haddad_ElaineGaspareto_M.pdf: 1752527 bytes, checksum: 6ecf36f9a07b62f0718f185c0fd4ca43 (MD5) Previous issue date: 1997<br>Resumo: Este trabalho aborda o problema de seqüenciamento de tarefas conhecido como Job Shop Scheduling Problem (JSP). O objetivo aqui é mostrar a adequação de uma técnica conhecida como Times Assíncronos (A-Teams), para resolver este prob
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Jain, Anant Singh. "A multi-level hybrid framework for the deterministic job-shop scheduling problem." Thesis, University of Dundee, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321923.

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Moratori, Patrick. "Match-up strategies and fuzzy robust scheduling for a complex dynamic real world job shop scheduling problem." Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/13054/.

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This thesis investigate a complex real world job shop scheduling / rescheduling problem, in which the presence of uncertainties and the occurrence of disruptions are tackled to produce efficient and reliable solutions. New orders arrive every day in the shop floor and they have to be integrated in the existent schedule. Match-up algorithms are introduced to collect the idle time on machines and accommodate these newly arriving orders. Their aim is to obtain new schedules with good performance which are at the same time highly stable, meaning that they resemble as closely as possible the initia
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Books on the topic "Job Shop Scheduling Problem (JSSP)"

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Fisher, Marshall L. Group Theory in the General N/m Job-Shop Problem. Creative Media Partners, LLC, 2018.

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Book chapters on the topic "Job Shop Scheduling Problem (JSSP)"

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Assafra, Khadija, Bechir Alaya, Salah Zidi, and Mounir Zrigui. "VGATS-JSSP: Variant Genetic Algorithm and Tabu Search Applied to the Job Shop Scheduling Problem." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_30.

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Albrecht, Andreas, Uwe Der, Kathleen Steinhöfel, and Chak-Kuen Wong. "Distributed Simulated Annealing for Job Shop Scheduling." In Parallel Problem Solving from Nature PPSN VI. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45356-3_24.

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Lemonias, H. D., and Z. Binder. "Decomposition Approach for the Job-Shop Scheduling Problem." In CAD/CAM Robotics and Factories of the Future ’90. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58214-1_19.

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Lemonias, H. D., and Z. Binder. "Decomposition Approach for the Job-Shop Scheduling Problem." In CAD/CAM Robotics and Factories of the Future ’90. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-85838-3_90.

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Singh, Shekhar, and Krishna Pratap Singh. "Cuckoo Search Optimization for Job Shop Scheduling Problem." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2217-0_9.

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Li, Xinyu, and Liang Gao. "A Hybrid Algorithm for Job Shop Scheduling Problem." In Engineering Applications of Computational Methods. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-55305-3_6.

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Jin, Feng, Shiji Song, and Cheng Wu. "Structural Property and Meta-heuristic for the Flow Shop Scheduling Problem." In Computational Intelligence in Flow Shop and Job Shop Scheduling. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02836-6_1.

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Ripon, Kazi Shah Nawaz, Chi-Ho Tsang, and Sam Kwong. "An Evolutionary Approach for Solving the Multi-Objective Job-Shop Scheduling Problem." In Evolutionary Scheduling. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-48584-1_7.

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Tasgetiren, M. Fatih, Quan-Ke Pan, P. N. Suganthan, Yun-Chia Liang, and Tay Jin Chua. "Metaheuristics for Common due Date Total Earliness and Tardiness Single Machine Scheduling Problem." In Computational Intelligence in Flow Shop and Job Shop Scheduling. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02836-6_10.

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Wang, Zhen, Jihui Zhang, and Jianfei Si. "Dynamic Job Shop Scheduling Problem with New Job Arrivals: A Survey." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9050-1_75.

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Conference papers on the topic "Job Shop Scheduling Problem (JSSP)"

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Lukas, Samuel, and Aditya Mitra. "Brute Force Algorithms for Job Shop Scheduling Problem." In 2024 2nd International Conference on Technology Innovation and Its Applications (ICTIIA). IEEE, 2024. https://doi.org/10.1109/ictiia61827.2024.10761790.

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Zhang, Jin, and Xiaohang Han. "Research on job assigning rules for dynamic distributed job-shop scheduling problem." In Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), edited by Pierluigi Siano and Wenbing Zhao. SPIE, 2024. http://dx.doi.org/10.1117/12.3033387.

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Abir, BELMAMOUNE Manal, YAHOUNI Zakaria, and GHOMRI Latéfa. "Optimization of Job Tardiness for Job Shop Scheduling Problem Using Reinforcement Learning." In 2024 International Conference of the African Federation of Operational Research Societies (AFROS). IEEE, 2024. https://doi.org/10.1109/afros62115.2024.11036729.

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Rodler, Patrick, Erich Teppan, and Dietmar Jannach. "Randomized Problem-Relaxation Solving for Over-Constrained Schedules." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/72.

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Optimal production planning in the form of job shop scheduling problems (JSSP) is a vital problem in many industries. In practice, however, it can happen that the volume of jobs (orders) exceeds the production capacity for a given planning horizon. A reasonable aim in such situations is the completion of as many jobs as possible in time (while postponing the rest). We call this the Job Set Optimization Problem (JOP). Technically, when constraint programming is used for solving JSSPs, the formulated objective in the constraint model can be adapted so that the constraint solver addresses JOP, i.
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Xu, Ke, and Souran Manoochehri. "Job Shop Scheduling Optimization Using Genetic Algorithm With Global Criterion Technique." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98076.

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Abstract The Job Shop Scheduling Problem (JSSP) is a method which assigns multiple jobs to various machines. The large dimension of JSSP and the dynamic manufacturing environment have always been a difficult problem to optimize due to its size and complexity. In this study, three objective functions are selected namely, minimizing makespan, minimizing total cost and maximizing machine utilization. Genetic Algorithm (GA) is used to solve this scheduling problem. Lot size optimization technique is investigated for the potential of optimizing the makespan, total cost, and machine utilization obje
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QUEIROZ, GABRIEL ANDRADE, and EDERSON ROSA DA SILVA. "UM ESTUDO COMPARATIVO ENTRE O NSGA-II E UM ALGORITMO GENÉTICO PARA A SOLUÇÃO DE UM JOB-SHOP SCHEDULING PROBLEM." In XXI CEEL – Conferência de Estudos em Engenharia Elétrica. Universidade Federal de Uberlândia, 2023. http://dx.doi.org/10.56316/2596-2221.xxi.ceel.786.

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Os problemas de escalonamento de processos possuem grande valor no estudo de otimização computacional aplicada a diversas áreas como redes de comunicação, infraestrutura, planejamento e logística. Por serem problemas classificados como de grande dificuldade combinatória, a aplicação de métodos heurísticos como algoritmos genéticos é uma boa escolha na busca de soluções. Assim, este estudo tem como objetivo analisar o emprego de algoritmos genéticos, destacando o NSGA-II, na solução do problema de otimização combinatória multiobjetivo JSSP. Os resultados expõem uma comparação de um algoritmo ge
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Morinaga, Eiji, and Atsuya Oda. "An Improved Method for Job Shop Scheduling by Means of Machine Learning and Mathematical Optimization." In 2024 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/isfa2024-141179.

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Abstract This paper is concerned with solving a job shop scheduling problem (JSSP) optimally in a shorter time by predicting a good solution based on a database of scheduling performed previously and then providing it as an initial solution in the optimization algorithm. Although several methods based on this framework have been developed, they have a problem that a considerable time is required for building learners. For reduction of learning time, an improved method using multiclass classification is provided in this paper. By numerical evaluation, it was shown that the learners in the propo
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Tamura, Yasumasa, Ikuo Suzuki, Masahito Yamamoto, and Masashi Furukawa. "The Hybrid Approach of LCO and SA to Solve Job-Shop Scheduling Problem." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7226.

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A Job-shop Scheduling Problem (JSP) is one of the combinatorial optimization problems. JSP appears as a basic scheduling problem in many situations of a manufacturing system and many methods for JSP have been invented. This study examines two effective methods, SA and LCO, for JSP and propose a hybrid method based on them. As a result of the experiments, the proposed method can find a good solution with short computational time. And the proposed method can hold the variance of the solutions less than the fundamental methods. Summarizing this study, the proposed method can find a good solution
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Camacho, Margareth, Yadira Velastegui, and Kleber Barcia. "A mathematical model for the optimization of the capacity of machinery and labor: Job Shop Scheduling Problem (JSSP) model." In 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions”. Latin American and Caribbean Consortium of Engineering Institutions, 2022. http://dx.doi.org/10.18687/laccei2022.1.1.91.

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Khalfa, Sana, Nizar Rokbani, Achraf Jabeur Telmoudi, and Lotfi Nabli. "A new approach based on Global Velocity Particle Swarm Optimization to solve job-shop scheduling problems, PSO-VG-JSSP." In 2016 International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2016. http://dx.doi.org/10.1109/codit.2016.7593619.

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Reports on the topic "Job Shop Scheduling Problem (JSSP)"

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Sadeh, Norman, Katia Sycara, and Yalin Xiong. Backtracking Techniques for the Job Shop Scheduling Constraint Satisfaction Problem. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada289435.

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Sadeh, Norman M., and Mark S. Fox. Variable and Value Ordering Heuristics for the Job Shop Scheduling Constraint Satisfaction Problem. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada311303.

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Fontes, Dalila, S. Mahdi Homayouni, and Joao Fernandes. Energy-efficient job shop scheduling problem with transport resources considering speed adjustable resources. Peeref, 2023. http://dx.doi.org/10.54985/peeref.2307p3639977.

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