Production scheduling and lot streaming at flexible job-shops environments using constraint programming

Novas, Juan M.

doi:10.1016/j.cie.2019.07.011

Cited by 48 publications

(19 citation statements)

References 29 publications

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“…Currently, production companies use a variety of planning methods, modules, and techniques based on deterministic algorithms, while evaluating different performance measures [13][14][15]: completion of production, flow time, delivery times, etc. As deterministic algorithms do not include numerous uncertainties from the real environment, such as machine failure, occurrence of scrap and so on, it is necessary to provide a certain type of support that will enable better and, above all, simpler production planning and management.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulationoptimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%.

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Section: Background and Literature Reviewmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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“…Equation (8) indicates that the start processing time of all job batches can start from zero. Equation (9) indicates that the size of each sub-batch of one job is not greater than its demand amount. Equation (10) indicates that the number of sub-batches of one job is not greater than its demand amount.…”

Section: Formulation Of Fjsp-vbmentioning

confidence: 99%

“…According to different job shop types, batch scheduling can be categorized into the parallel machine batch scheduling problem [3,4], the flow shop batch scheduling problem [5−8], the job shop batch scheduling problem [9], and the flexible job shop batch scheduling problem [10−17]. Since Reiter [18] first introduced the concept of "batch flow" in the context of the job shop scheduling problem in 1966, the scheduling problem considering batch production has attracted increasing interest from authors.…”

Section: Introductionmentioning

confidence: 99%

An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches

Peng

Zirun

et al. 2021

J. of Syst. Eng. Electron.

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In order to solve the flexible job shop scheduling problem with variable batches, we propose an improved multiobjective optimization algorithm, which combines the idea of inverse scheduling. First, a flexible job shop problem with the variable batches scheduling model is formulated. Second, we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method. Moreover, in order to increase the diversity of the population, two methods are developed. One is the threshold to control the neighborhood updating, and the other is the dynamic clustering algorithm to update the population. Finally, a group of experiments are carried out. The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively, and has effective performance in solving the flexible job shop scheduling problem with variable batches.

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“…Reference [5] discussed real-world applications of scheduling problems where steel needs to be cooled to form slabs. Reference [16] and [17] solved the issue of lot streaming in FJSP, where batches of the jobs were split into subplots to allow the overlapping of operations.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Genetic Algorithm for Flexible Job Shop Scheduling Problem With Sequence-Dependent Setup Times and Job Lag Times

Wang

Zhu

2021

IEEE Access

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This paper addresses the flexible job shop scheduling problem with sequence-dependent setup times and job lag times (FJSP-SDST-LT), which characteristics are important in modern manufacturing systems. We first present a mathematical model with the objective to minimize the makespan. Then a hybrid algorithm (HGA-TS) which combines genetic algorithm (GA) and tabu search (TS) is proposed to solve the FJSP-SDST-LT. The GA performs powerful global search by genetic operators and serves as exploration, while based on the specific structure of SDST and LT, the TS is able to perform an effective local search by relocating operations and serves as exploitation. Therefore, the proposed HGA-TS integrates good searching ability with strong diversifying ability. In order to solve the FJSP-SDST-LT effectively, we adopt effective encoding and decoding methods, genetic operators in GA, and four neighborhood structures in TS. We conduct computational experiments on two classes of instances generated from two classic data sets and the results show the great performance of HGA-TS in solving FJSP-SDST-LT.

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Production scheduling and lot streaming at flexible job-shops environments using constraint programming

Cited by 48 publications

References 29 publications

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

An improved multi-objective optimization algorithm for solving flexible job shop scheduling problem with variable batches

A Hybrid Genetic Algorithm for Flexible Job Shop Scheduling Problem With Sequence-Dependent Setup Times and Job Lag Times

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