检索结果-内蒙古大学图书馆

Multi-objective optimization of complex scheduling problems in low-volume low-variety production systems

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2019年 208卷 1-16页

作者： Russell, Arya Taghipour, Sharareh Ryerson Univ 350 Victoria St Toronto ON M5B 2K3 Canada

In this paper, a new approach for solving scheduling problems in low-volume low-variety production systems is proposed. Products assembled in such production systems follow a pre-defined processing order through a series of unique work centers, each budgeted with multiple classifications of resources, responsible to complete a pre-defined statement of work, over the span of an imposed takt-time. Aircraft, heavy aero-structures, and heavy mining and military equipment are examples of products assembled in such production systems. Despite prominent scholarly advancements in sequencing and scheduling optimization of a wide range of production systems, limited research has been reported on mathematical programming approaches for scheduling optimization of activities in low-volume low-variety production systems. This paper fills the gap in the current literature, through the formulation of a set of multi-objective mixed-integer linear mathematical programming models, developed for solving discrete-time work center scheduling problems in low-volume low-variety production systems. Three mathematical models are proposed in this paper, two of which are formulated for scheduling optimization of activities within a work center, differentiated by their objectives and underlying assumptions, reflective of two distinct industrial approaches to scheduling. Additionally, an alternative optimization model is proposed for evaluating a work center's maximum capacity given the complete saturation of resources, recommended for capacity studies and early detection of bottlenecks. The models proposed in this paper are validated and verified for compatibility and reliability through a real-world case study with a global leader in the aerospace industry.

关键词： Low-volume low-variety production systems Large-scale optimization Scheduling optimization Multi-objective programming mixed-integer programming Aerospace assembly line

来源：评论

学校读者我要写书评

暂无评论

Polyhedral results and valid inequalities for the continuous energy-constrained scheduling problem

引用

DISCRETE APPLIED MATHEMATICS 2019年 258卷 188-203页

作者： Nattaf, Margaux Horvath, Marko Kis, Tamas Artigues, Christian Lopez, Pierre Univ Toulouse LAAS CNRS CNRS Toulouse France Hungarian Acad Sci Inst Comp Sci & Control Budapest Hungary

This paper addresses a scheduling problem involving a continuously-divisible cumulative resource with limited capacity. During its processing, each task requests a part of this resource, which lies between a minimum and a maximum requirement. A task is finished when a certain amount of energy is received by it within its time window. This energy is received via the resource and an amount of resource is converted into an amount of energy with an increasing and pseudo-linear efficiency function. The goal is to minimize the resource consumption. The paper focuses on an event-based mixed integer linear program, providing several valid inequalities, which are used to improve the performance of the model. Furthermore, we give a minimal description of the polytope of all feasible assignments to the on/off binary variable for a single activity along with a dedicated separation algorithm. Computational experiments are reported in order to show the effectiveness of the results. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Continuous scheduling Continuous resources Linear efficiency functions mixed-integer programming Valid inequalities Polyhedral combinatorics

来源：评论

学校读者我要写书评

暂无评论

Analysis of models for the Stochastic Outpatient Procedure Scheduling Problem

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第3期279卷 721-731页

作者： Shehadeh, Karmel S. Cohn, Amy E. M. Epelman, Marina A. Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

In this paper, we present a new stochastic mixed-integer linear programming model for the Stochastic Outpatient Procedure Scheduling Problem (SOPSP). In this problem, we schedule a day's worth of procedures for a single provider, where each procedure has a known type and associated probability distribution of random duration. Our objective is to minimize the expectation of a weighted sum of patient waiting time, provider idling, and clinic overtime. We present computational results to show the size and characteristics of problem instances that can be solved with our model. We also compare this model to other formulations in the literature and analyze them both empirically and theoretically, demonstrating where significant improvements in performance can be gained with our proposed model. This work is motivated by our research on developing scheduling templates for endoscopic procedures at a major medical center. More broadly, however, the SOPSP is a stochastic single-resource sequencing and scheduling problem and therefore has applications both within and outside of healthcare operations. (C) 2019 Elsevier B.V. All rights reserved.

关键词： OR in health services Appointment scheduling Outpatient clinics Stochastic programming mixed-integer programming

来源：评论

学校读者我要写书评

暂无评论

COVID-19: Agent-based simulation-optimization to vaccine center location vaccine allocation problem

A I I E Transactions

引用

A I I E Transactions 2024年第7期56卷

作者： Xuecheng Yin Sabah Bushaj Yue Yuan İ. Esra Büyüktahtakın a Management Science and Information Systems Oklahoma State University Norman OK USA b School of Business and Economics SUNY Plattsburgh Plattsburgh New York USA c Altfest Personal Wealth Management NY USA d Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg VA USA

This article presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location–allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework co

关键词： Agent-based simulation optimization vaccination center facility location vaccine allocation vaccine distribution mixed-integer programming COVID-19 SIR model epidemiological model supply chain and logistics

来源：评论

学校读者我要写书评

暂无评论

Bi-objective cyclic scheduling for single hoist with processing-time-window constraints considering buffer-setting

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2019年第2期233卷 192-203页

作者： Gao, Zhongshun Zhou, Binghai Tongji Univ Sch Mech Engn Shanghai 201804 Peoples R China

To solve the scheduling problem of a single hoist with processing-time-window constraints considering buffer-setting, we consider bi-objective scheduling which makes trade-offs between the cycle time and the hoist travel distance. First, a bi-objective mixed-integer programming model is constructed for the basic line without considering buffer-setting. In order to improve the throughput of the basic line, a transform method with buffer-setting is put forward. Based on the basic line model, a subsection searching epsilon-constraint method which combines the transform method is introduced to solve the bi-objective mixed-integer programming model. Experimental results both on benchmark instances and on randomly generated instances indicate that the proposed approach is efficient and buffers can improve the throughputs.

关键词： Bi-objective buffer-setting epsilon-constraint method hoist-scheduling problem mixed-integer programming

来源：评论

学校读者我要写书评

暂无评论

The Airlift Planning Problem

引用

TRANSPORTATION SCIENCE 2019年第3期53卷 773-795页

作者： Bertsimas, Dimitris Chang, Allison Misic, Velibor V. Mundru, Nishanth MIT Sloan Sch Management 77 Massachusetts Ave Cambridge MA 02139 USA MIT Operat Res Ctr 77 Massachusetts Ave Cambridge MA 02139 USA MIT Lincoln Lab Lexington MA 02420 USA Univ Calif Los Angeles Anderson Sch Management Los Angeles CA USA

The U.S. Transportation Command (USTRANSCOM) is responsible for planning and executing the transportation of U.S. military personnel and cargo by air, land, and sea. The airlift planning problem faced by the air component of USTRANSCOM is to decide how requirements (passengers and cargo) will be assigned to the available aircraft fleet and the sequence of pickups and drop-offs that each aircraft will perform to ensure that the requirements are delivered with minimal delay and with maximum utilization of the available aircraft. This problem is of significant interest to USTRANSCOM because of the highly time-sensitive nature of the requirements that are typically designated for delivery by airlift, as well as the very high cost of airlift operations. At the same time, the airlift planning problem is extremely difficult to solve because of the combinatorial nature of the problem and the numerous constraints present in the problem (such as weight restrictions and crew rest requirements). In this paper, we propose an approach for solving the airlift planning problem faced by USTRANSCOM based on modern, large-scale optimization. Our approach relies on solving a large-scale mixed-integer programming model that disentangles the assignment decision (which aircraft will pickup and deliver which requirement) from the sequencing decision (in what order the aircraft will pickup and deliver its assigned requirements), using a combination of heuristics and column generation. Through computational experiments with both a simulated data set and a planning data set provided by USTRANSCOM, we show that our approach leads to high-quality solutions for realistic instances (e.g., 100 aircraft and 100 requirements) within operationally feasible time frames. Compared with a baseline approach that emulates current practice at USTRANSCOM, our approach leads to reductions in total delay and aircraft time of 8%-12% in simulated data instances and 16%-40% in USTRANSCOM's planning instances.

关键词： pickup and delivery with time windows mixed-integer programming column generation local search construction heuristics

来源：评论

学校读者我要写书评

暂无评论

Massive MIMO Optimization With Compatible Sets

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第5期18卷 2794-2812页

作者： Fitzgerald, Emma Pioro, Michal Tufvesson, Fredrik Lund Univ Dept Elect & Informat Technol SE-22100 Lund Sweden Warsaw Univ Technol Inst Telecommun PL-00665 Warsaw Poland

Massive multiple-input multiple-output (MIMO) is expected to be a vital component in future 5G systems. As such, there is a need for new modeling in order to investigate the performance of massive MIMO not only at the physical layer but also higher up the networking stack. In this paper, we present general optimization models for massive MIMO, based on mixed-integer programming and compatible sets, with both maximum ratio combining and zero-forcing precoding schemes. We then apply our models to the case of joint device scheduling and power control for heterogeneous devices and traffic demands, in contrast to the existing power control schemes that consider only homogeneous users and saturated scenarios. Our results show that substantial benefits, in terms of energy usage, can be achieved without sacrificing throughput and that both the signaling overhead and the complexity of end devices can be reduced by abrogating the need for uplink power control through efficient scheduling.

关键词： Massive MIMO scheduling power control mixed-integer programming compatible sets massive machine type communications

来源：评论

学校读者我要写书评

暂无评论

Anticipation versus reactive reoptimization for dynamic vehicle routing with stochastic requests

引用

NETWORKS 2019年第3期73卷 277-291页

作者： Ulmer, Marlin W. Tech Univ Carolo Wilhelmina Braunschweig Carl Friedrich Gauss Fak Braunschweig Germany

Due to new business models and technological advances, dynamic vehicle routing is gaining increasing interest. Especially solving dynamic vehicle routing problems with stochastic customer requests becomes increasingly important, for example, in e-commerce and same-day delivery. Solving these problems is challenging, because it requires optimization along two dimensions. First, as a reaction to new customer requests, current routing plans need to be reoptimized. Second, potential future requests need to be anticipated in current decision making. Decisions need to be derived in real-time. The limited time often prohibits extensive optimization in both dimensions and the question arises how to utilize the limited calculation time effectively. In this paper, we analyze the merits of reactive route reoptimization and anticipation for a dynamic vehicle routing problem with stochastic requests. To this end, we compare an existing method from each dimension as well a policy allowing for a tunable combination of the two approaches. We show how the appropriate optimization combination is strongly connected to the degree of dynamism, the percentage of unknown requests. We also show that our combination does not provide significant benefit compared to the respectively best optimization dimension.

关键词： anticipation approximate dynamic programming degree of dynamism dynamic vehicle routing mixed-integer programming reoptimization stochastic requests

来源：评论

学校读者我要写书评

暂无评论

A Configuration-Component-Based Hybrid Model for Combined-Cycle Units in MISO Day-Ahead Market

引用

IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第2期34卷 883-896页

作者： Dai, Chenxi Chen, Yonghong Wang, Fengyu Wan, Jie Wu, Lei Clarkson Univ Elect & Comp Engn Dept Potsdam NY 13699 USA Midcontinent Independent Syst Operator Inc Carmel IN 46032 USA GE Grid Software Solut Redmond WA 98052 USA

This paper proposes a hybrid combined-cycle gas turbine (CCGT) model for day-ahead market clearing, in order to enhance the operation flexibility of CCGTs in practice. The proposed hybrid model, by taking benefits of combined offers from market participants on both configurations and individual physical turbines, can more accurately reflect physical operation features of CCGTs than existing CCGT models. A comprehensive review on existing CCGT models in academia and industry practice with their advantages and shortcomings is conducted. By taking benefits of the two most investigated models, i.e., configuration-based model and component-based model, the mapping relationship between these two models is revealed for deriving the proposed hybrid model. Tight formulations are further discussed for achieving the better computational performance. The proposed hybrid model is tested and compared with other CCGT models via the modified IEEE 118-bus system and the midcontinent independent system operator system. Results show notable benefits in maintaining operation flexibility and enhancing social welfare.

关键词： Combined-cycle gas turbine hybrid model mixed-integer programming security-constrained unit commitment tight formulation

来源：评论

学校读者我要写书评

暂无评论

Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery

引用

TRANSPORTATION SCIENCE 2019年第1期53卷 236-255页

作者： Klein, Robert Neugebauer, Michael Ratkovitch, Dimitri Steinhardt, Claudius Univ Augsburg D-86159 Augsburg Germany Bundeswehr Univ Munich D-85577 Neubiberg Germany

In this paper, we study an e-grocer's tactical problem of differentiated time slot pricing in attended home delivery. The purpose of differentiating delivery prices is to influence customers' choice behavior concerning the offered time slots, such that cost-effective delivery schedules on an operational level can be expected and overall profit is maximized. We present a mixed-integer linear programming formulation of the problem, in which delivery costs are anticipated by explicitly incorporating routing constraints, and we model customer behavior by a general nonparametric rank-based choice model. Concerning cost anticipation, we also propose a model-based approximation that enables application to real-world problem sizes. In a setup inspired by an industry partner operating in urban areas, we then perform a comprehensive computational study that reveals the value of the model-based approximation as a supporting instrument for an e-grocer's pricing decisions in practice. In particular, we demonstrate the superiority of the model-based approximation for real-world problem sizes to several benchmark approaches applied in the scientific literature and in practice (e.g., a unit price approach and other standard pricing heuristics).

关键词： e-grocery attended home delivery delivery time slots differentiated pricing vehicle routing mixed-integer programming

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：