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Che Han Lim and Seung Ki Moon
In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of au...
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Yuri N. Sotskov, Natalja M. Matsveichuk and Vadzim D. Hatsura
We study two-machine shop-scheduling problems provided that lower and upper bounds on durations of n jobs are given before scheduling. An exact value of the job duration remains unknown until completing the job. The objective is to minimize the makespan ...
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Shubhendu Kshitij Fuladi and Chang-Soo Kim
In the real world of manufacturing systems, production planning is crucial for organizing and optimizing various manufacturing process components. The objective of this paper is to present a methodology for both static scheduling and dynamic scheduling. ...
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Yu-Hung Chang, Chien-Hung Liu and Shingchern D. You
The dynamic flexible job-shop problem (DFJSP) is a realistic and challenging problem that many production plants face. As the product line becomes more complex, the machines may suddenly break down or resume service, so we need a dynamic scheduling frame...
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Pavel V. Matrenin
Planning tasks are important in construction, manufacturing, logistics, and education. At the same time, scheduling problems belong to the class of NP-hard optimization problems. Ant colony algorithm optimization is one of the most common swarm intellige...
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Atabak Elmi, Dhananjay R. Thiruvady and Andreas T. Ernst
Cyclic scheduling is of vital importance in a repetitive discrete manufacturing environment. We investigate scheduling in the context of general cyclic job shops with blocking where there are no intermediate buffers between the machines. We also consider...
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Danial Rooyani and Fantahun Defersha
The work in this paper is motivated by a recently published article in which the authors developed an efficient two-stage genetic algorithm for a comprehensive model of a flexible job-shop scheduling problem (FJSP). In this paper, we extend the applicati...
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Mingming Xu, Shuning Zhang and Guanlong Deng
When no-wait constraint holds in job shops, a job has to be processed with no waiting time from the first to the last operation, and the start time of a job is greatly restricted. Using key elements of the iterated greedy algorithm, this paper proposes a...
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Marvin Carl May, Alexander Albers, Marc David Fischer, Florian Mayerhofer, Louis Schäfer and Gisela Lanza
Currently, manufacturing is characterized by increasing complexity both on the technical and organizational levels. Thus, more complex and intelligent production control methods are developed in order to remain competitive and achieve operational excelle...
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Jiri Stastny, Vladislav Skorpil, Zoltan Balogh and Richard Klein
In this paper we introduce the draft of a new graph-based algorithm for optimization of scheduling problems. Our algorithm is based on the Generalized Lifelong Planning A* algorithm, which is usually used for path planning for mobile robots. It was teste...
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Bruno Cunha, Ana Madureira, Benjamim Fonseca and João Matos
In this paper, we present and discuss an innovative approach to solve Job Shop scheduling problems based on machine learning techniques. Traditionally, when choosing how to solve Job Shop scheduling problems, there are two main options: either use an eff...
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Hongchan Li, Haodong Zhu and Tianhua Jiang
In recent decades, workshop scheduling has excessively focused on time-related indicators, while ignoring environmental metrics. With the advent of sustainable manufacturing, the energy-aware scheduling problem has been attracting more and more attention...
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Piotr Jedrzejowicz and Izabela Wierzbowska
One of the possible approaches to solving difficult optimization problems is applying population-based metaheuristics. Among such metaheuristics, there is a special class where searching for the best solution is based on the collective behavior of decent...
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Alessandro Agnetis, Fabrizio Rossi and Stefano Smriglio
We address some special cases of job shop and flow shop scheduling problems with s-precedence constraints. Unlike the classical setting, in which precedence constraints among the tasks of a job are finish?start, here the task of a job cannot start before...
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Xiaolin Gu, Ming Huang and Xu Liang
For solving the complex flexible job-shop scheduling problem, an improved genetic algorithm with adaptive variable neighborhood search (IGA-AVNS) is proposed. The improved genetic algorithm first uses a hybrid method combining operation sequence (OS) ran...
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Julia Lange and Frank Werner
The job shop scheduling problem with blocking constraints and total tardiness minimization represents a challenging combinatorial optimization problem of high relevance in production planning and logistics. Since general-purpose solution approaches strug...
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Ping Liu, Qiang Zhang and Jürgen Pannek
With the development of industrial manufacture in the context of Industry 4.0, various advanced technologies have been designed, such as reconfigurable machine tools (RMT). However, the potential of the latter still needs to be developed. In this paper, ...
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Atif Shahzad and Nasser Mebarki
A promising approach for an effective shop scheduling that synergizes the benefits of the combinatorial optimization, supervised learning and discrete-event simulation is presented. Though dispatching rules are in widely used by shop scheduling practitio...
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Jian Li, Huankun Li, Pengbo He, Liping Xu, Kui He and Shanhui Liu
Green manufacturing has become a new production mode for the development and operation of modern and future manufacturing industries. The flexible job shop scheduling problem (FJSP), as one of the key core problems in the field of green manufacturing pro...
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Paolo Renna
The reduction in emissions and the increase in energy costs push companies to identify solutions to reduce energy consumption in production systems. One of the approaches proposed in the literature is the shutdown of machines to reduce energy consumption...
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