Application of an improved Lagrangian relaxation approach in the constrained long-term production scheduling problem under grade uncertainty

Tolouei, Kamyar; Moosavi, Ehsan; Tabrizi, Amir Hossein Bangian; Afzal, Peyman

doi:10.1080/0305215x.2020.1746295

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…Since the reform and opening up, combined with the law of industrial adjustment, Guiyang has actively promoted the transformation of industrial structure from low level to high level [3]. In the development of the three industries, from the perspective of output value composition as shown in Figure 1, the proportion of the primary industry dropped from 20% to 13%, the proportion of the secondary industry dropped from 60% to 47%, and the tertiary industry increased by 20 percentage points [4]; the structural characteristics of Gansu's modern economy are becoming more and more obvious, but compared with developed areas, there are still problems such as the low proportion of service industry, uncoordinated development among the three industries, and insignificant role of modern industrial sectors [5].…”

Section: Introductionmentioning

confidence: 98%

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

2022

Mobile Information Systems

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In the field of econometrics, panel data are an extremely important type of data. In macroeconomic research, panel data models are widely used in exchange rate determination theory, testing of cross-border economic growth and convergence theory, analysis of industrial structure, research on technological innovation, etc. The agglomeration and population distribution of colleges and universities, and the economic support of industrial parks play an important role in economic and social development as a source of research and development and a source of talents. The panel data model usually assumes that the error term follows a normal distribution, but the actual data are difficult to satisfy this assumption, and the estimation obtained by traditional methods may be biased or even invalid. This paper proposes a more robust and effective estimation method (ELS-EL) based on the panel data mean regression model, and extends this method to complex panel data models such as generalized linear models and partial linear models; in addition, this paper is based on panel data. We proposed a two-stage instrumental variable method (2S-IVFEQR) to reduce the computational complexity and generalized the new method to the quantile regression model of dynamic panel data. At the same time, this paper uses the above-improved panel data econometric model to analyze the spatial spillover effects of college aggregation, population distribution, and industrial parks in Guiyang. This study found that the agglomeration of colleges and universities has significantly promoted the economic growth of our country. These promotion effects come from both the direct contribution of college agglomeration and the positive external spillover effect of college agglomeration.

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Section: Introductionmentioning

confidence: 98%

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

2022

Mobile Information Systems

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“…The problem difficulty increases rapidly with the increase in problem size. The LR heuristic is an algorithm that can efficiently solve integer or mixed-integer optimization models and has been proven to be an effective technique in a variety of applications (Beasley 1993;Liu, Li, and Liu 2017;Wang, Liu, and Zheng 2020;Tolouei et al 2020;Hamdan and Diabat 2020;Zhang et al 2020). By relaxing the complicating constraints and adding them to the objective function, this method provides a lower bound to the original optimization model (for a minimization problem) (Fisher 1985).…”

Section: Lagrangian Relaxation Algorithmmentioning

confidence: 99%

A queuing–location–allocation model for designing a capacitated bus garage system

Chen

Yao

Chen

et al. 2021

Engineering Optimization

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The spatial distribution of bus garages determines the total vehicular dead mileage of the transit system because buses must travel between bus garages and terminals at the start or conclusion of a day. By contrast, the size of the garages determines the queuing status when buses enter or leave the garages. Thus, a bus garage system with reasonable distribution and size is required to address these problems. In this article, a queuing-location-allocation model for optimizing a bus garage system is developed. Since a nonlinear objective function is involved, a linearization technique is introduced to convert the proposed model into an equivalent linear form. Next, a Lagrangian relaxation algorithm is designed to solve the linear form model. To validate the proposed algorithm, two groups of randomly generated test instances and a real-life case, the Dalian transit system in China, are applied. The results show that the proposed Lagrangian heuristic is efficient and stable.

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“…Therefore, the DAPFSP with completion time as the objective function is also a strong NP-hard problem. In recent years, as a simple yet efficient method, the bat algorithm has solved many scheduling problems in academia, including the job shop scheduling problem [1], the open shop scheduling problem [2], the task scheduling problem [3], and the production scheduling problem [4], by continuously performing local search in the neighborhood of the current solution to obtain the optimal solution.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Bat Algorithm for Solving the Three-Stage Distributed Assembly Permutation Flowshop Scheduling Problem

Zheng

Wang

2021

Applied Sciences

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In this paper, a hybrid bat optimization algorithm based on variable neighbourhood structure and two learning strategies is proposed to solve a three-stage distributed assembly permutation flowshop scheduling problem to minimize the makespan. The algorithm is firstly designed to increase the population diversity by classifying the populations, which solves the difficult trade-off between convergence and diversity of the bat algorithm. Secondly, a selection mechanism is used to update the bat’s velocity and location, solving the difficulty of the algorithm to trade-off exploration and mining capacity. Finally, the Gaussian learning strategy and elite learning strategy assist the whole population to jump out of the local optimal frontier. The simulation results demonstrate that the algorithm proposed in this paper can well solve the DAPFSP. In addition, compared with other metaheuristic algorithms, IHBA has better performance and gives full play to its advantage of finding optimal solutions.

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Application of an improved Lagrangian relaxation approach in the constrained long-term production scheduling problem under grade uncertainty

Cited by 10 publications

References 16 publications

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

Application and Analysis of Spatial Spillover Effects of an Improved Panel Data Econometric Model in Universities, Population, and Industrial Parks in Guiyang

A queuing–location–allocation model for designing a capacitated bus garage system

A Hybrid Bat Algorithm for Solving the Three-Stage Distributed Assembly Permutation Flowshop Scheduling Problem

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