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ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on programming and Software (Onward!)

作者： Bragg, Nate F. F. Foster, Jeffrey S. Zucker, Philip Tufts Univ Medford MA 02155 USA Draper Lab Cambridge MA USA

ISBN: (纸本)9798400712159

mixed integer linear programming is a powerful and widely used approach to solving optimization problems, but its expressiveness is limited. In this paper we introduce the optimization-aided language SCIMITAR, which encodes optimization problems using an expressive functional language, with a compiler that targets a mixed integer linear program solver. SCIMITAR provides easy access to encoding techniques that normally require expert knowledge, enabling solve-time conditional constraints, inlining, loop unrolling, and many other high-level language constructs. We give operational semantics for SCIMITAR and constraint encodings of various features. To demonstrate SCIMITAR, we present a number of examples and benchmarks including classic optimization domains and more complex problems. Our results indicate that SCIMITAR's use of a dedicated MILP solver is effective for expressively modeling optimization problems embedded within functional programs.

关键词： mixed integer linear programming functional programming compilers

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Fragment Allocations for Partially Replicated Databases Considering Data Modifications and Changing Workloads 24

Fragment Allocations for Partially Replicated Databases Cons...

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33rd ACM International Conference on Information and Knowledge Management (CIKM)

作者： Halfpap, Stefan Schlosser, Rainer TU Berlin BIFOLD Berlin Germany Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9798400704369

Columnar database systems can process complex mixed workloads on a single node. In case of increasing and peak analytical processing demand, we can offload read-only queries to replicas. Partial replication, i.e., duplicating only data subsets to additional nodes, is more cost-efficient than full replication for two primary reasons: (i) Partial replicas require less storage and can be set up faster. (ii) Partial replicas must synchronize only stored data subsets, allowing better scalability. However, determining which queries to offload is challenging for larger workloads because queries access overlapping data subsets and cause synchronization costs. This paper shows how to calculate optimized replica configurations that consider reallocation and data modification costs using integer linear programming (ILP) techniques. While ILP is effective for solving assignment problems, it does not scale well. For larger problems, users often fall back to simple heuristics, which can lose optimization potential. This paper demonstrates that scalable heuristics can be built on ILP, preserving its strengths. The three proposed approaches for reducing the calculation time allow trading solution quality flexibly. Our evaluations using TPC-H, TPC-DS, and a large real-world accounting workload show that our approach outperforms state-of-the-art solutions, often reducing re=allocated data by more than 80% and halving modification costs. At the same time, the new allocations reduce the storage consumption by over 30%, with solutions computed in just a few seconds.

关键词： partial replication mixed integer linear programming

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Virtual Target Selection for a Multiple-Pursuer Multiple-Evader Scenario

Virtual Target Selection for a Multiple-Pursuer Multiple-Eva...

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AIAA SciTech Forum

作者： Weintraub, Isaac E. Von Moll, Alexander Casbeer, David Manyam, Satyanarayana G. US Air Force Res Lab Control Sci Ctr Wright Patterson AFB OH 45433 USA Infoscitex Corp Dayton OH 45431 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper considers an M-pursuer N-evader scenario involving virtual targets. The virtual targets serve as an intermediary target for the pursuers, allowing the pursuers to delay their final assignment to the evaders. However, upon reaching the virtual target, the pursuers must decide which evader to capture. It is assumed that there are more pursuers than evaders and that the pursuers are faster than the evaders. The objective is two-part: first, assign each pursuer to a virtual target and evader such that the pursuer team's energy is minimized, and second, choose the virtual targets' locations for this minimization problem. The approach taken is to consider the Apollonius geometry between each pursuer's virtual target location and each evader. Using the constructed Apollonius circles, the pursuer's travel distance and maneuver at a virtual target are obtained. These metrics serve as a gauge for the total energy required to capture a particular evader and are used to solve the joint virtual target selection and pursuer-evader assignment problem. This paper provides a mathematical definition of this problem, the solution approach taken, and an example.

关键词： mixed integer linear programming Optimal Control Theory Weapon Target Assignment linear programming Heuristic Approach Reinforcement Learning Computing Cost Guidance Laws

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A simulation optimization method for coordination of production, transportation and sales

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FUNDAMENTAL RESEARCH 2025年第2期5卷 473-485页

作者： Zheng, Yi Lei, Ming Peng, Yijie Peking Univ Guanghua Sch Management Beijing 100871 Peoples R China

This study considers a problem of coordinating production, transportation and sales in a multi-echelon supply chain network. A simulation model is built to generate the random customer demands at different locations, which are affected by a marketing strategy. Customer demands need to be satisfied by the supply chain through production, transportation and distribution. The optimization problem for coordination of production, transportation and distribution is first formulated as a linear programming with demands as input parameters in the constraint. Our objective is to maximize the expectation of the optimal profit of the supply chain given random demands by selecting an optimal marketing strategy. A simulation optimization technique is proposed to control the generation of random demands and solve the linear programming for efficiently learning the optimal marketing strategy. Numerical results show that our method can significantly improve the expected profit of the supply chain and reduce the computational burden of solving linear programming for achieving a given level of probability of correct selection of the optimal marketing strategy. Furthermore, we extend the optimization problem to a mixed integer programming and also demonstrate the computational efficiency of our proposed method.

关键词： Supply chain coordination Marketing strategy Simulation optimization linear programming mixed integer linear programming

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Optimal Design of Battery, Charging Infrastructure Planning, and Charging Scheduling for Electric Bus Network

Optimal Design of Battery, Charging Infrastructure Planning,...

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14th Conference on Traffic and Granular Flow (TGF)

作者： Pangtey, Tanisha Gairola, Pranav Nezamuddin, N. Indian Inst Technol Delhi Dept Civil Engn New Delhi 110016 India

ISBN: (纸本)9789819979783;9789819979769;9789819979752

Recognizing the growing global threat of air pollution, transit agencies and governments across the world are focusing on switching to electric vehicles (EVs). Battery electric buses (BEB) are becoming a crucial component to plan a sustainable transportation system. Two biggest drawbacks of BEBs are range anxiety and higher charging time. To overcome these hurdles, decision-makers are required to execute strategic decisions such as planning and design of charging locations as well as operational decisions like scheduling the charging activities for BEBs. This study gives insight into the planning and design of charging infrastructure network for BEBs while minimizing the total annual cost of designing the BEB system Apart from this, this study also focuses on the scheduling part for BEBs and provide information on the occurrence of charging activities for BEBs. A mixed-integer linear programming model is formulated which models the trade-off between route-specific battery capacity and terminal-level charging power (charger size along with the number of chargers at a terminal) and generates a scheduling plan for charging the BEBs. A part of New Delhi's public bus network identified for electrification (18 bus routes and 21 terminal stations) by its transit agency was selected for our model application. Results suggested that model was able to obtain trade-off between battery size allocation and charger size selection.

关键词： BEB mixed integer linear programming Fast charging

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Optimal Residential Community Demand Response Scheduling Based on User Preferences and MILP 36

Optimal Residential Community Demand Response Scheduling Bas...

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36th Chinese Control and Decision Conference (CCDC)

作者： Peng, Qiya Li, Xiaohui Mao, Shanli Cai, Bin He, Jie Nie, Wei Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan Peoples R China Wuhan Netizen Technol Co Ltd Res Ctr Wuhan Peoples R China Shenglong Elect Grp Co Ltd Res Ctr Wuhan Peoples R China

ISBN: (纸本)9798350387780;9798350387797

Demand response manages energy demand to match available energy in the smart grid. Residential community loads in the smart grid are diverse and flexible. To integrate user preferences with demand response scheduling for residential communities, a centralized demand response scheduling algorithm is proposed. In this paper, user willingness price is first introduced through fuzzy c-means to quantify user preferences. Secondly, a complete residential community DR scheduling algorithm is established based on use preference and mixed integer linear programming to minimize the total energy cost of the residential community. Simulation results show that the proposed algorithm can reduce the total energy cost of the residential community and communication traffic.

关键词： smart residential community demand response mixed integer linear programming user willingness price

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A Time-Dependent Subgraph-Capacity Model for Multiple Shortest Paths and Application to CO2/Contrail-Safe Aircraft Trajectories

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Operations Research Forum 2024年第3期5卷 71页

作者： Demouge, Céline Mongeau, Marcel Couellan, Nicolas Delahaye, Daniel ENAC Université de Toulouse 7 Avenue Edouard Belin Toulouse 31400 France Institut Mathématiques de Toulouse UMR 5219 Université de Toulouse CNRS UPS Toulouse Cedex 9 31062 France

This paper proposes a study motivated by the problem of minimizing the environmental impact of air transport considering the complete air network, thereby several aircraft. Both CO2 and non-CO2 effects are taken into account to calculate this impact. The proposed methodology takes a network point of view in which airspace capacities evolve as well as the traffic itself over time. Finding the shortest path with numerous constraints and various cost functions is a common problem in operations research. This study deals with the special case of multiple shortest paths with capacity constraints on a time-dependent subgraph. Multiple shortest paths are understood as one shortest path per vehicle considered. The static special case is modeled as a mixed integer linear program so that it can be efficiently solved by standard off-the-shelf optimization solvers. The time-dependent nature of the problem is then modeled via a sliding-window approach. Encouraging numerical results on the contrail-avoidance application show that the environmental impact can be significantly reduced while maintaining safety by satisfying the airspace capacity constraints. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Air transportation Contrails mixed integer linear programming Subgraph constrained time-dependent shortest-path problem

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Comparison of efficient procedures for hydropower unit commitment

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ENERGY REPORTS 2022年 8卷 2472-2479页

作者： Wang, Jinwen Zheng, Hao Feng, Suzhen Chen, Cheng Liu, Shuangquan Wang, Youxiang Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Joint Int Water Secur Res Ctr Wuhan 430074 Hubei Peoples R China Yunnan Elect Power Dispatch & Control Ctr Kunming 650001 Yunnan Peoples R China

This paper explores three new competitive heuristic procedures, which are compared with the mixed integer linear programming (MILP), all used to commit units within a hydroplant to give the maximal electrical production during a study horizon, given the cascade operation has already determined the quarter-hourly releases from individual reservoirs. The problem incorporates constraints on the unit up/down hours and its shutdown times. The procedures are applied to seven hydroplants, with 2, 3, 4, 5, 6, 9 and 18 units installed respectively. The application suggests that the MILP performs the best in minimizing spillages and improving generating efficiency but volatile in computation time when the number of units is more than 4 in a hydroplant, while the heuristic procedures can obtain fairly good results and have a significant advantage in computation time when committing more than 6 units in a hydroplant. The heuristic procedures are valuable when incorporating unit commitment into a large-scale operational problem of cascaded hydropower reservoirs. (C) 2022 The Authors. Published by Elsevier Ltd.

关键词： Large-scale hydropower reservoir system Hydropower unit commitment mixed integer linear programming Heuristic procedures Computational burden Spillage reduction

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Job-Shop Scheduling with Robot Synchronization for Transport Operations 15th

Job-Shop Scheduling with Robot Synchronization for Transport...

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15th International Conference of the Metaheuristics International Conference (MIC)

作者： Gayon, Jean Philippe Lacomme, Philippe Oussama, Amine Univ Clermont Auvergne LIMOS Clermont Auvergne INP CNRSMines St Etienne F-63000 Clermont Ferrand France

ISBN: (纸本)9783031629112;9783031629129

We consider a Job Shop Scheduling Problem with transport (JSPT) which consists in jointly scheduling machines and robots. In contrast with the literature, we assume that a transport operation may involve several robots simultaneously, which requires resource synchronization over time. We formulate this problem as a mixed integer linear programming (MILP) formulation. Then we propose a GRASP-ELS meta-heuristic and a local search procedure where we use a Bierwith's sequence approach to evaluate a solution. In a numerical study, we have adapted instances from the literature to our problem. The meta-heuristic competes with the exact resolution providing high quality solution in reduced computation time, which lead us to consider that both the modeling and local search are accurate.

关键词： Job shop Synchronization Scheduling Transportation Disjunctive graph Meta-heuristic mixed integer linear programming

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Enhanced Power System Restoration Through MILP Black Start Allocation Optimization 5

Enhanced Power System Restoration Through MILP Black Start A...

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5th Annual IEEE Kansas Power and Energy Conference (KPEC)

作者： Kabir, Shaharier Shufian, Abu Islam, Riadul Hannan, Nasif Zishan, Md Saniat Rahman Fattah, Shaikh Anowarul Amer Int Univ Bangladesh Dept EEE Dhaka Bangladesh Lamar Univ Beaumont TX USA Bangladesh Univ Engn & Technol Dhaka Bangladesh

ISBN: (纸本)9798350372410;9798350372403

Restoring a power system following a blackout is a critical undertaking, necessitating the efficient allocation of Black Start (BS) resources-generators capable of initiating without external power. This research introduces an innovative approach to address a critical challenge in power system restoration-optimal black start allocation. Efficient allocation of resources when power systems face blackouts is crucial for rapid restoration. Leveraging the power of mixed integer linear programming (MILP), this study formulates and solves the black start allocation problem with the primary objective of minimizing allocation costs, all while satisfying many operational constraints. These constraints include ensuring power supply meets demand, adhering to generator output limits and ramping rates, and enforcing time-bound generator startup decisions. Furthermore, it maintains power flow equilibrium and network stability through branch flow and voltage magnitude constraints. This research offers a promising solution to enhance the resilience and reliability of power systems by optimizing the allocation of black start resources. This would reduce downtime ultimately and mitigate the far-reaching impacts of blackouts on society and the economy.

关键词： Power System Restoration mixed integer linear programming Black Start Allocation Optimal Scheduling

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