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5th International Conference on Industrial Engineering and Systems Management (IEEE IESM)

作者： Pellegrini, Paola Douchet, Guillaume Marliere, Gregory Rodriguez, Joaquin Univ Lille Nord France Ifsttar ESTAS F-59666 Lille France

ISBN: (纸本)9782960053241

In railway traffic management, when an unexpected event perturbs the system, finding an effective train routing and scheduling in real-time is a key issues. Making the right routing and scheduling decisions may have a great impact on the efficiency of the system in terms of delay propagation. However, the time available for making these decisions is quite short: in few minutes a viable set of routes and schedules must be delivered to the dispatching system. In this paper, we assess the performance of a mixed integer linear programming (MILP) formulation exploited as a heuristic approach: we seek for the best feasible solution given a limited and predefined computation time. We run an experimental analysis on instances representing traffic in the Lille Flandres station, France. The results show that the approach tested is very promising, often finding the optimal solution to the instances tackled. Moreover, we show how the performance can be improved by tuning the parameters of the MILP solver.

关键词： mixed integer linear programming scheduling system Network routing TRAIN Heuristics computational time optimal solution railway transportation management

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mixed integer linear programming Model for Scheduling Burn-in Ovens to Minimize Total Weighted Earliness/Lateness

Mixed Integer Linear Programming Model for Scheduling Burn-i...

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Recent Advances and Innovations in Engineering (ICRAIE)

作者： Dhaval Jayendrakumar Pujara Muthu Mathirajan Indian Institute of Science Bengaluru India

ISBN: (数字)9781728188676

ISBN: (纸本)9781728188683

This study deals with scheduling of Burn-in Oven (BO), a Batch Processing Machine (BPM) in the testing stage of Semiconductor Manufacturing (SM) process. We consider a new problem configuration, close to real-life machining environment, wherein multiple BOs having different capacity are employed parallelly to process the variety of jobs. Jobs have non-agreeable release date & due date, non-identical processing time and non-identical job size. An early completion of job at BO is penalized with earliness penalty whereas late completion of job at BO causes a lateness penalty. In the current Just in Time (JIT) manufacturing scenario, an organization aims to minimize both the penalties (cost). Hence, this study aims to minimize the total weighted earliness/lateness of the jobs. We propose a mixed integer linear programming (MILP) model for dynamic scheduling of (a) single, and (b) multiple BOs. Each of the proposed MILP are validated by developing a suitable numerical example.

关键词： Job shop scheduling Ovens Computational modeling Dynamic scheduling Numerical models mixed integer linear programming Manufacturing

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mixed integer linear programming Trajectory Generation for Autonomous Nap-of-the-Earth Flight in a Threat Environment

Mixed Integer Linear Programming Trajectory Generation for A...

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IEEE Conference on Aerospace

作者： C.S. Ma R.H. Miller Northrop Grumman Integrated Systems El Segundo CA USA

This paper extends a recently developed approach to the optimal path planning of an autonomous vehicle in an obstacle field to three dimensions with specific applications to terrestrial navigation, with obstacle, terrain, and threat avoidance. We present a scenario where this approach can be applied to a rotorcraft performing nap-of-the-Earth flight in challenging terrain with multiple known surface threats, in both urban and non-urban type settings. mixed-integer linear programming (MILP) is the underlying problem formulation, from which an optimal solution can be obtained through the use of a commercially available MILP solver such as CPLEX. The solution obtained would be optimal in terms of the cost function specified in terms of fuel, time, altitude and threat exposure, and other predefined criteria. A receding horizon implementation of this MILP algorithm makes it suitable for real-time or near real-time applications

关键词： mixed integer linear programming Path planning linear programming Remotely operated vehicles Mobile robots Trajectory Mathematical programming Mathematical model Paper technology Navigation

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The Planning of Distribution Network Containing Distributed Generators Based on mixed integer linear programming 5

The Planning of Distribution Network Containing Distributed ...

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5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Shi, Jinyue Qiao, Ying Wang, Yingrui Wen, Junqiang Tong, Jingjing Zhang, Jianhua North China Elect Power Univ Sch Elect & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781467371063

currently, the methods for solving the planning of distribution network (DN) are meta-heuristic algorithms whose computational efficiency is low and the results are not accurate. Therefore, this paper uses the advanced mixed integer linear programming (MILP) technology to model the multi-conductor DN planning containing the allocation of distributed generator (DG). Firstly, replace power flow calculation with an equivalent cone programming, then remove the product terms of binary and continuous variables, and finally use polyhedral models which are linear to approximate the planning model. In addition, as the siting and sizing of DG are added to the network planning, the situation that part of the loads are supplied by the DG separately perhaps appear thus leading to the appearance of loops. So the spanning tree (ST) constraints are introduced to the model to ensure the radiation of the DN. Finally, 23-node distribution system is used to simulate the above-mentioned model, and the results show the effectiveness and efficiency of the proposed model.

关键词： distributed generator mixed integer linear programming distribution network planning multi-conductor planning spanning tree constraints

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Optimal Sizing of Distributed Energy Resources in Smart Microgrids: a mixed integer linear programming Formulation 6

Optimal Sizing of Distributed Energy Resources in Smart Micr...

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6th IEEE INTERNATIONAL CONFERENCE on RENEWABLE ENERGY RESEARCH and APPLICATIONS (ICRERA 2017)

作者： Scalfati, Andrea Iannuzzi, Diego Fantauzzi, Maurizio Roscia, Mariacristina DIETI University of Naples Federico II Napoli Italy DII University of Naples Federico II Napoli Italy Department of Engineering and Applied Sciences University of Bergamo Bergamo Italy

ISBN: (纸本)9781538620953

Microgrids can offer various benefits to electricity consumers, but these benefits must he compared with the corresponding investment cost for ensuring financial feasibility. This paper is focused on the problem of optimally sizing, from an economic perspective, the Distributed Energy Resources included in a DC Microgrid, determining the optimal niix of Distributed Generators and Energy Storage Systems, taking also into account the opportunities of Load Management. The proposed procedure is based on mixed integer linear programming and allows to determine the optimal sizes of Distributed Energy Resources which minimize the Microgrid Total Cost of Ownership, given location and load characteristics. The procedure is formulated as a quite general method that can he used for different microgrid architectures and different generation and storage technologies, although in this paper it is applied to a grid-connected DC microgrid with PV generation and storage system. Results of numerical applications to a case study demonstrate the effectiveness of the proposed sizing procedure.

关键词： Design optimization Distributed Energy Resources Load management Microgrid planning mixed integer linear programming Smart Microgrids

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Integrating random regret minimization-based discrete choice models with mixed integer linear programming for revenue optimization

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Iran Journal of Computer Science 2024年第1期8卷 21-35页

作者： Talebi, Amirreza Haeri Boroujeni, Sayed Pedram Razi, Abolfazl Department of Integrated Systems Engineering The Ohio State University Columbus OH United States School of Computing Clemson University Clemson 29632 SC United States ENSIMAG Grenoble Alpes University Grenoble France

This paper explores the critical domain of revenue management (RM) within operations research (OR), focusing on intricate pricing dynamics. Utilizing mixed integer linear programming (MILP) models, the study enhances revenue optimization by considering product prices as decision variables and emphasizing the interplay between demand and supply. Recent advancements in discrete choice models (DCMs), particularly those rooted in random regret minimization (RRM) theory, are investigated as potent alternatives to established random utility maximization (RUM)-based DCMs. Despite the widespread use of DCMs in RM, a significant gap exists between cutting-edge RRM-based models and their practical integration into RM strategies. The study addresses this gap by incorporating an advanced RRM-based DCM into MILP models, addressing pricing challenges in both capacitated and uncapacitated supply scenarios. The developed models demonstrate the feasibility and offer diverse interpretations of consumer choice behavior, drawing inspiration from established RUM-based frameworks. This research contributes to bridging the existing gap in the application of advanced DCMs within practical RM implementations. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2024.

关键词： Choice-based optimization Decision-making behavior Demand prediction mixed integer linear programming Operations research Pricing

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Solving a Malleable Jobs Scheduling Problem to Minimize Total Weighted Completion Times by mixed integer linear programming Models 8th

Solving a Malleable Jobs Scheduling Problem to Minimize Tota...

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8th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

作者： Nhan-Quy Nguyen Yalaoui, Farouk Amodeo, Lionel Chehade, Hicham Toggenburger, Pascal Univ Technol Troyes LOSI ICD UMR 6281CNRS 12 Rue Marie CurieBP 2060 F-10010 Troyes France Opta LP 2 Rue Gustave Eiffel F-10430 Rosieres Pres Troyes France ParknPlug 13 Rue Marie Curie F-10430 Rosieres Pres Troyes France

ISBN: (纸本)9783662493908;9783662493892

In this paper we report two mixed integer linear programming models to resolve the malleable jobs scheduling problem with single resource. Jobs' release dates and deadlines are taken into account. The total amount of available resource of the system is variable at different times. Numerical experimentation is conducted to evaluate the performance variability between two introduced models. The objective of this optimization problem is to minimize the total weighted completion time.

关键词： mixed integer linear programming Malleable jobs Scheduling Total weighted completion times minimization

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Research on Task Allocation of Multi-constraint Unmanned System Swarm Based on mixed integer linear programming

Research on Task Allocation of Multi-constraint Unmanned Sys...

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International Conference on Autonomous Unmanned Systems (ICAUS)

作者： Tu, Long Liu, Shulei Yan, Ye Yao, Wen Chang, Qiang Natl Innovat Inst Def Technol Beijing Peoples R China Xidian Univ Xian Peoples R China

ISBN: (纸本)9789819904815;9789819904792;9789819904785

Unmanned systems swarm task allocation is one of the key issues of unmanned systems collaborative control. Aiming at the multiple objectives and multiple constraints task allocation issue of unmanned systems swarm, under the multi-constrained conditions of comprehensively considering the benefits of unmanned systems swarm against multiple targets, weapon costs, disabling costs, time costs and energy costs, taking the largest net income, the smallest number of unmanned systems dispatched, and the least number of weapons carried by unmanned systems as the optimization goals respectively, the mathematical models of multi-constrained task allocation based on mixed integer linear programming is established. The Cplex solver is used to solve the specific examples. And the calculation results are analyzed. The results show that the task allocation model based on "platform-weapon-target" can effectively solve the assignment issue of multi-constraint unmanned system swarm.

关键词： Mission planning mixed integer linear programming Task allocation

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Multi-Period Optimization of Hybrid Energy Systems Using mixed integer linear programming

Multi-Period Optimization of Hybrid Energy Systems Using Mix...

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IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)

作者： Alhashedi, Salah Khan, Khalid A. Alowaifeer, Maad Khalid, Muhammad King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia KFUPM Ctr Renewable Energy & Power Syst Dhahran 31261 Saudi Arabia KFUPM SDAIA KFUPM Joint Res Ctr Artificial Intelligence Dhahran 31261 Saudi Arabia

ISBN: (纸本)9798350332117

The integration of hybrid energy systems (HES) into the electric power grid is gaining traction due to the need of establishing a clean and sustainable energy system for satisfying the increasing load demand. Such integration enables integration of renewable energy sources in the form of HES that is scalable from small as well as large-scale integration. Nevertheless, the commonly preferred renewable energy sources (RESs), such as, solar and wind energy have significantly limited economic feasibility owing to their unpredictability and intermittency. Energy storage systems (ESSs) are among the key solutions to mitigate the impact of variable renewable energy sources on the grid by acting as an energy buffer. In this paper, a multiperiod optimization technique is formulated for the appropriate scheduling of ESSs in a HES that acts as a model of a residential district consisting of several houses with installed PV systems and connections to the main electricity grid. To further verify the method's effectiveness, the results are obtained for both summer and winter season scenarios.

关键词： Energy storage systems hybrid energy system mixed integer linear programming multi-period optimization solar photovoltaics

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A Finite-Time Cutting Plane Algorithm for Distributed mixed integer linear programming 56

A Finite-Time Cutting Plane Algorithm for Distributed Mixed ...

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56th Annual IEEE Conference on Decision and Control (CDC)

作者： Testa, Andrea Rucco, Alessandro Notarstefano, Giuseppe Univ Salento Dept Engn Lecce Italy

ISBN: (纸本)9781509028733

Many problems of interest for cyber-physical network systems can be formulated as mixed integer linear Programs in which the constraints are distributed among the agents. In this paper we propose a distributed algorithm to solve this class of optimization problems in a peer-to-peer network with no coordinator and with limited computation and communication capabilities. In the proposed algorithm, at each communication round, agents solve locally a small LP, generate suitable cutting planes, namely intersection cuts and cost-based cuts, and communicate a fixed number of active constraints, i.e., a candidate optimal basis. We prove that, if the cost is integer, the algorithm converges to the lexicographically minimal optimal solution in a finite number of communication rounds. Finally, through numerical computations, we analyze the algorithm convergence as a function of the network size.

关键词： Distributed algorithms Optimization Convergence Algorithm design and analysis mixed integer linear programming Routing

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