Study on the Scheduling Problem of Powder Painting Production - A Case Study

2010 ◽  
Vol 97-101 ◽  
pp. 2459-2464
Author(s):  
Zhang Yong Hu ◽  
Qiang Su ◽  
Jun Liu ◽  
Hai Xia Yang
Keyword(s):  
Large Scale ◽  
Production Efficiency ◽  
Production Performance ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Adaptive Search ◽  
Optimal Sequence ◽  
Integer Nonlinear Programming ◽  
Minlp Model

A large-scale powder-painting scheduling problem is explored. The purpose is to find out the optimal sequence of a number of batches that dynamically arrive from upstream processes within a given scheduling horizon. The objective is to enhance the production efficiency and decrease the production cost as well. To solve this problem, a mixed integer nonlinear programming (MINLP) model is constructed and an algorithm called greedy randomized adaptive search procedure (GRASP) is designed. Case studies demonstrate that the proposed approach can improve the production performance significantly.

Schedule Coordination Method for Last Train Transfer Problem

2017 ◽  
Vol 2648 (1) ◽  
pp. 86-95 ◽  
Author(s):  
Xueping Dou ◽  
Xiucheng Guo
Keyword(s):  
Transfer Problem ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Transit System ◽  
Schedule Coordination ◽  
Urban Rail ◽  
Integer Nonlinear Programming ◽  
Minlp Model ◽  
Optimization Solvers

This paper proposes a schedule coordination method for last train service in an urban rail transit system. The method offsets and perturbs the original train schedule to reduce transfer failures across different lines, and it considers the effect of schedule adjustments. The proposed problem is formulated as a mixed-integer nonlinear programming (MINLP) model. The MINLP model is equivalently transformed into a mixed-integer linear programming (MILP) model that can be exactly solved by commercial optimization solvers. A case study based on the mass rapid transit system in Singapore was conducted. The results of the case study indicate that the train schedule that is coordinated by the developed model is capable of substantially improving operational connectivity. Therefore, the model proposed in this study can be employed as a viable tool to assist with the coordination of train schedules for public transport operators.

scholarly journals MINLP formulations for continuous piecewise linear function fitting

2021 ◽  
Author(s):  
Noam Goldberg ◽  
Steffen Rebennack ◽  
Youngdae Kim ◽  
Vitaliy Krasko ◽  
Sven Leyffer
Keyword(s):  
Linear Function ◽  
Piecewise Linear ◽  
Piecewise Linear Function ◽  
Mixed Integer ◽  
Function Fitting ◽  
Computational Performance ◽  
Integer Nonlinear Programming ◽  
Minlp Model ◽  
Necessary Constraints ◽  
Continuous Piecewise Linear Function

AbstractWe consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523–541, 2014. 10.1007/s10589-014-9647-y) for piecewise linear function fitting. We show that this MINLP model is incomplete and can result in a piecewise linear curve that is not the graph of a function, because it misses a set of necessary constraints. We provide two counterexamples to illustrate this effect, and propose three alternative models that correct this behavior. We investigate the theoretical relationship between these models and evaluate their computational performance.

Application of UF/NF for the treatment of CIP (cleaning in place) rinsing waters: case study in a liquid detergent production plant

2003 ◽  
Vol 3 (5-6) ◽  
pp. 283-288
Author(s):  
M. Forstmeier ◽  
T. Schipolowski ◽  
B. Goers ◽  
G. Wozny
Keyword(s):  
Nonlinear Programming ◽  
Sheet Material ◽  
Mixed Integer ◽  
Production Plant ◽  
Plant Structure ◽  
Water Network ◽  
Liquid Detergent ◽  
Flat Sheet ◽  
Integer Nonlinear Programming

In this paper the applicability of ultrafiltration and nanofiltration for the treatment of rinsing water in a liquid detergent plant has been investigated. Suitable membranes have been found in a membrane screening with flat sheet material, pilot experiments with industrial spiral wound modules under realistic conditions have shown the membranes' potential for reducing the COD load in the wastewater by up to 96%. Finally an optimum membrane plant structure has been derived by mixed integer nonlinear programming optimisation based on the experimental results. The membrane plant has been integrated into a model of the water network according to the concept for retrofit optimization of water networks strategy.

scholarly journals Solving the Short-Term Scheduling Problem of Hydrothermal Systems via Lagrangian Relaxation and Augmented Lagrangian

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Rafael N. Rodrigues ◽  
Edson L. da Silva ◽  
Erlon C. Finardi ◽  
Fabricio Y. K. Takigawa
Keyword(s):  
Lagrangian Relaxation ◽  
Large Scale ◽  
Augmented Lagrangian ◽  
Augmented Lagrangian Method ◽  
Real Life ◽  
Hydrothermal Systems ◽  
Bundle Method ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Short Term

This paper addresses the short-term scheduling problem of hydrothermal power systems, which results in a large-scale mixed-integer nonlinear programming problem. The objective consists in minimizing the operation cost over a two-day horizon with a one-hour time resolution. To solve this difficult problem, a Lagrangian Relaxation (LR) based on variable splitting is designed where the resulting dual problem is solved by a Bundle method. Given that the LR usually fails to find a feasible solution, we use an inexact Augmented Lagrangian method to improve the quality of the solution supplied by the LR. We assess our approach by using a real-life hydrothermal configuration extracted from the Brazilian power system, proving the conceptual and practical feasibility of the proposed algorithm. In summary, the main contributions of this paper are (i) a detailed and compatible modelling for this problem is presented; (ii) in order to solve efficiently the entire problem, a suitable decomposition strategy is presented. As a result of these contributions, the proposed model is able to find practical solutions with moderate computational burden, which is absolutely necessary in the modern power industry.

Risk-Averse Optimization for Resilience Enhancement Under Uncertainty

2020 ◽  
Author(s):  
Jiaxin Wu ◽  
Pingfeng Wang
Keyword(s):  
Large Scale ◽  
Risk Measure ◽  
Recovery Process ◽  
Recovery Phase ◽  
Mixed Integer ◽  
Network Systems ◽  
Additional Risk ◽  
Deterministic Equivalent ◽  
Study Results

Abstract With the growth of complexity and extent, large scale interconnected network systems, e.g., transportation networks or infrastructure networks, become more vulnerable towards external disturbances. Hence, managing potential disruptive events during design, operating, and recovery phase of an engineered system therefore improving the system’s resilience is an important yet challenging task. In order to ensure system resilience after the occurrence of failure events, this study proposes a mixed integer linear programming (MILP) based restoration framework using heterogenous dispatchable agents. Scenario based stochastic optimization (SO) technique is adopted to deal with the inherent uncertainties imposed on the recovery process from the nature. Moreover, different from conventional SO using deterministic equivalent formulations, additional risk measure is implemented for this study because of the temporal sparsity of the decision making in applications such as the recovery from extreme events. The resulting restoration framework involves with a large-scale MILP problem and thus an adequate decompaction technique, i.e., modified Langragian Relaxation, is also proposed in order to achieve tractable time complexity. Case study results based on the IEEE 37-buses test feeder demonstrate the benefits of using the proposed framework for resilience improvement as well as the advantages of adopting SO formulations.

scholarly journals Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

2019 ◽  
Vol 11 (17) ◽  
pp. 4713 ◽  
Author(s):  
Yuping Lin ◽  
Kai Zhang ◽  
Zuo-Jun Max Shen ◽  
Lixin Miao
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Cost Minimization ◽  
Transportation Network ◽  
Power Grid ◽  
Mixed Integer ◽  
Charging Infrastructure ◽  
Second Order Cone ◽  
Charging Stations

In 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a “No R” algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.

scholarly journals Research on the Radical Innovation of C2M Business Model—A Case Study on Redcollar MTM Men’s Suits in China

2016 ◽  
Vol 11 (4) ◽  
pp. 194 ◽  
Author(s):  
Yingfen Zhou ◽  
Ming Xu ◽  
Rong Di
Keyword(s):  
Business Model ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Production Efficiency ◽  
Value Added ◽  
Radical Innovation ◽  
High Tech ◽  
Scale Production ◽  
Traditional Manufacturing

<p class="AbstractWCCM"><span lang="EN-US">For recently years, with the deep integration of informatization and industrialization, traditional manufacturing industries in China have been investigating for the road of transformation and upgrading. A Chinese garment enterprise, named Redcollar Group of China, has successfully transformed and upgraded to high-tech industry with high value added from labor-intensive industry. It is very important to explore the reason, method and business model it has created so as to provide some beneficial advice to China’s traditional manufactures. In this case study, indirect research, field research, comparison research and customers’ experience methods have been used. As a result, it is found that the enterprise has successfully created a C2M business mode of men's custom suits and has succeeded in producing customization suits with large-scale production efficiency. Being the first factory in the world by using industrialization measures to produce thoroughly customized men’s suits, the Redcollar’s C2M model is the revolutionary and disruptive radical innovation which breaks through the traditional suits making, the traditional clothing manufacturing model, the value perception of traditional manufacturing industry and the existing business regulations. </span></p>

scholarly journals An Optimization-Based System Dynamics Simulation for Sustainable Policy Design in WEEE Management Systems

2021 ◽  
Vol 13 (20) ◽  
pp. 11377
Author(s):  
Camilo Llerena-Riascos ◽  
Sebastián Jaén ◽  
Jairo Rafael Montoya-Torres ◽  
Juan G. Villegas
Keyword(s):  
System Dynamics ◽  
Management System ◽  
Policy Design ◽  
Optimal Parameter ◽  
Environmental Benefits ◽  
Dynamics Simulation ◽  
Mixed Integer ◽  
Generation Process ◽  
Minlp Model

The increase in the use of electrical and electronic devices worldwide has created a rapid growth of waste of electrical and electronic equipment (WEEE). The current paper presents an optimization-based simulation (OBS) approach that allows the design of sustainable WEEE management system policies. The proposed OBS approach integrates a system dynamics (SD) model and a mixed-integer nonlinear programming (MINLP) model to improve the representation and performance of the WEEE processes considering their operative and strategic interdependence. The SD component elicits the complexity of the WEEE generation process. Complementarily, the MINLP model periodically optimizes key variables of the WEEE management system. Computational results in a case study based on WEEE from Colombian mobile phones illustrates how an approach solely based on SD simulation is unable to capture the operative-strategic nature of the system and perform optimal parameter updates. By contrast, the OBS approach of this paper outperforms an exclusive SD analysis both in the economic and environmental performance of the system. It obtains 33% more profits and 65% more environmental benefits. Moreover, for this case study, the model suggests that the cornerstone of the WEEE management system for increasing its performance is the replacement rate.

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