Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Geng, Kaifeng; Ye, Chunming; Dai, Zhen; Liu, Li

doi:10.1155/2020/8565921

Cited by 33 publications

(16 citation statements)

References 39 publications

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“…In this paper, the uniform speed of the vehicles is considered, where τ � 0, but the influence of the gradient of the vehicle is not considered. en, the per unit time of the vehicle t is shown in equation (6). erefore, the energy consumption of the transportation stage can be given as shown in equation (7), where the unit of speed is m/s:…”

Section: Energy Consumption Of Transportation Stage (Ec St2 )mentioning

confidence: 99%

“…e production process plays an important role in the manufacturing industry. In recent years, in order to reduce energy consumption in the production process, many studies have been conducted on improving the energy efficiency [2][3][4][5][6]. However, among the methods, production scheduling is the most effective and prioritized way to improve the energy efficiency of the manufacturing industry [7].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Estimation of Distribution Algorithm for Solving Three‐Stage Multiobjective Integrated Scheduling Problem

Deng

Qian

et al. 2021

Complexity

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Aiming at reducing the total energy consumption of three stages processing-transportation-assembly in the assembly manufacturing industry, a three-stage multiobjective integrated scheduling problem with job batch transportation considering the energy consumption (3sMISP_JBTEC) is proposed, and a comprehensive energy consumption model of multistage of 3sMISP_JBTEC with an improved turn off/on strategy in the processing stage and considering speed in the transportation stage is formulated. Then, a hybrid estimation of distribution algorithm with variable neighborhood search (HEDA_VNS) is developed to solve the scheduling problem. In the HEDA_VNS, the reasonable coding/decoding rules and speed scheduling scheme (SSS) are designed. Moreover, two local search strategies are designed to further enhance the performance of HEDA_VNS. Among them, three types of neighborhood search strategies are devised in Local Search I to improve the search efficiency while retaining the structure of the original high-quality solution. A variable neighborhood hybrid operation based on the speed scheduling set is designed in Local Search II to further improve the quality of the solution while balancing the optimization goals. Finally, simulations and comparisons show the efficiency of the proposed HEDA_VNS.

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Section: Energy Consumption Of Transportation Stage (Ec St2 )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Estimation of Distribution Algorithm for Solving Three‐Stage Multiobjective Integrated Scheduling Problem

Deng

Qian

et al. 2021

Complexity

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“…Geng and al. (2020) [11] developed a two-objective optimization model for a hybrid flow-shop type scheduling problem considering the energy consumption costs based on the time of use (TOU) of electricity. Gong and al.…”

Section: Introductionmentioning

confidence: 99%

The combination of a NEH heuristic and an LP metric to solve a flow-shop scheduling problem taking into account energy consumption and production costs: a case study

2022

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In this work, we study a multi-objective problem in a pharmaceutical production unit composed of several production stations that produce several kinds of products. The goal of this work, in a first step, is to propose a scheduling at the production unit in order to establish a synchronization of the different tasks on the m-machines. The problem can be formulated by the scheduling of a multi-product flow-shop.Then, we take into account the energy constraints of each task to be done. The problem can be formulated by a linear multi-objective MILP program, where the first objective is to determine the best sequence that minimizes the production and launch costs. In addition, the second objective is to find the best sequence that minimizes energy consumption. The problem is formulated and solved by combining the NEH heuristic and the LP-metric method to determine an intermediate solution between minimizing production costs and minimizing energy consumption.

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“…[8−12] used a neural network to solve different scheduling problems. Reference [13] adopted reinforcement learning based approaches to multi-objective dynamic scheduling. Reference [14] presented an inductive learning method based real-time scheduling mechanism for reentrant hybrid flow shops.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Hybrid Flow Shop Scheduling Approach in Smart Manufacturing Environment

Chen

2021

Complex Syst. Model. Simul.

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Smart manufacturing in the "Industry 4.0" strategy promotes the deep integration of manufacturing and information technologies, which makes the manufacturing system a ubiquitous environment. However, the real-time scheduling of such a manufacturing system is a challenge faced by many decision makers. To deal with this challenge, this study focuses on the real-time hybrid flow shop scheduling problem (HFSP). First, the characteristic of the hybrid flow shop in a smart manufacturing environment is analyzed, and its scheduling problem is described. Second, a real-time scheduling approach for the HFSP is proposed. The core module is to employ gene expression programming to construct a new and efficient scheduling rule according to the realtime status in the hybrid flow shop. With the scheduling rule, the priorities of the waiting job are calculated, and the job with the highest priority will be scheduled at this decision time point. A group of experiments are performed to prove the performance of the proposed approach. The numerical experiments show that the realtime scheduling approach outperforms other single-scheduling rules and the back-propagation neural network method in optimizing most objectives for different size instances. Therefore, the contribution of this study is the proposal of a real-time scheduling approach, which is an effective approach for real-time hybrid flow shop scheduling in a smart manufacturing environment.

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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Cited by 33 publications

References 39 publications

Hybrid Estimation of Distribution Algorithm for Solving Three‐Stage Multiobjective Integrated Scheduling Problem

Hybrid Estimation of Distribution Algorithm for Solving Three‐Stage Multiobjective Integrated Scheduling Problem

The combination of a NEH heuristic and an LP metric to solve a flow-shop scheduling problem taking into account energy consumption and production costs: a case study

Real-Time Hybrid Flow Shop Scheduling Approach in Smart Manufacturing Environment

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