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Mathematical programming-Based Design Structure Matrix Clustering for Optimal Modular Architecture Design

Journal of Mechanical Design 2025年第10期147卷 101401页

作者： Kim, Jaewoo Choi, Euihyeon Ahn, Jaemyung Suh, Eun Suk Kim, Jeong-Hoon Lim, Dong Gyu Department of Aerospace Engineering Korea Advanced Institute of Science and Technology (KAIST) 291 Daehak-ro Yuseong-Gu Daejeon 34141 South Korea https://***/01zkghx44Georgia Institute of Technology North Avenue Atlanta GA 30332 Graduate School of Engineering Practice Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 South Korea Vehicle Architecture Module Planning Team Hyundai Motor Company 150 Hyundaiyeonguso-ro Hwaseong Gyeonggi-do 18280 South Korea

This article introduces a new mixed integer linear programming (MILP) approach to the modular architecture design problem based on the design structure matrix (DSM). The DSM modularization (clustering) problem aims to maximize the modularity (quantified by the Q-metric) under constraints reflecting practical design/manufacturing/maintenance considerations. A MILP formulation is developed to optimize a modular architecture under constraints. The developed formulation is verified through two case studies on the subsystems of an automobile and an electric train. Both case studies successfully demonstrate the proposed formulation's effectiveness, highlighting its practical applicability.

关键词： design optimization design structure matrix mixed integer linear programming Design systems engineering multi-objective optimization design for X modular architecture design decision theory constrained clustering

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Using mixed integer programming models to synchronously determine production levels and market prices in an integrated market for roundwood and forest biomass

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ANNALS OF OPERATIONS RESEARCH 2015年第1期232卷 179-199页

作者： Kong, Jiehong Roennqvist, Mikael Frisk, Mikael NHH Norwegian Sch Econ Dept Finance & Management Sci Bergen Norway Univ Laval Dept Mech Engn Quebec City PQ Canada Forestry Res Inst Sweden Uppsala Sweden

We study a problem of integrating the supply chain of roundwood with the supply chain of forest biomass. The developed optimization model is a multiperiod, multicommodity network planning problem with multiple sources of supply, i.e., harvest areas, and multiple types of destinations, i.e., sawmills, pulp mills, and heating plants. This paper presents an extension of previous work where the set of harvest areas was given and market prices for raw materials had linear relationship with corresponding volumes. In this paper, the assumption of predefined areas is removed, and we must make the selection of harvest areas. Instead of using a traditional sequential approach to first select areas and then determine the prices, we present a new synchronous approach that can jointly choose areas and define price levels for different assortments at those chosen supply points. We test the possible settings of discretized price and use sensitivity analysis to evaluate how the variation of fixed cost concerning log forwarding at each supply point affects the wood procurement decisions. A case study from Sweden is used to analyze the market prices in an integrated market. The computational results also highlight the advantage of the proposed synchronous approach over the sequential one in both solution quality and solution time.

关键词： Forestry supply chain Integrated market Forest biomass Wood procurement mixed integer linear programming

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Late Train-Crew Rescheduling—a Model and a Heuristic Approach

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Transportation Research Procedia 2025年 86卷 337-344页

作者： Liyun Yu Carl Henrik Häll Anders Peterson Christiane Schmidt Department of Science and Technology Linköping University Norrköping Sweden

In this paper, we reschedule the duties of train drivers one day before the operation. Due to absent drivers (e.g., because of sick leave), some trains have no driver. Thus, duties on the operation day need to be rescheduled. We start with a feasible crew schedule of the remaining operating drivers, a set of unassigned tasks which were assigned to the absent drivers, and a group of standby drivers with fixed start time, end time, start depot, and end depot. Our aim is to generate a crew schedule with as few cancelled driving tasks and changed tasks as possible. We developed a mixed integer linear programming (MILP) model for short-term crew rescheduling. We also present a Tabu-Search-Based approach with the same objective function and equivalent restrictions of our mathematical model. We compare the results of the MILP model solved by Gurobi 11.0 and of the Tabu-Search-Based approach. Our Tabu-Search-Based approach takes less time and memory occupation to compute a ‘good-enough’ result. We further test the performance of our approach under different circumstances. The data used in the experiments are real data provided by Mälartåg.

关键词： Railway crew rescheduling mixed integer linear programming Tabu search

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A VNS Approach For a Joint Fulfillment and Consolidation Problem in E-commerce

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Transportation Research Procedia 2025年 84卷 89-96页

作者： Kehinde G. Ismaila Adriana F. Gabor Andrei Sleptchenko Maher Maalouf Management Science and Engineering Department Khalifa University Abu Dhabi 127788 UAE Mathematics Department Khalifa University Abu Dhabi 127788 UAE

Recent advances in supply chain and logistics illustrate that consolidation of orders can considerably reduce transportation costs and CO2 emissions. In this paper, we study the impact of consolidation on order fulfillment in e-Commerce. We consider a retailer with an online platform and network of physical stores, who must decide the optimal locations from which to fulfill a set of multi-item orders, as well as the optimal consolidation points for each order. To model the economy of scale obtained by consolidating orders, we consider piecewise-linear concave transportation costs. Our model extends the existing literature by considering multiple orders at a time and stores with limited inventory. We formulate the problem as an MILP and propose a Variable Neighborhood Search (VNS) to find good quality solutions in a short time. We tested the performance of the proposed algorithm on different scenarios, where stores have a varying percentage of overlapping items. Via numerical experiment, we observed a 0.22% average relative increase in cost using VNS for instances with large overlap in items among stores and a 2.36% average relative increase for the other scenarios. On average, the VNS is 16 times faster than the MILP formulation

关键词： Consolidation Multi-Order mixed integer linear programming Variable Neighborhood Search Logistics

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Energy-Aware Blocking Hybrid Flow Shop Scheduling Problem with Sequence-depend Setup Times and Machine Speed Levels

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Procedia Computer Science 2025年 253卷 1134-1143页

作者： Ahmed Missaoui Cemalettin Ozturk Barry O’Sullivan Insight Centre for Data Analytics University College Cork Ireland Process Energy and Transport Engineering Munster Technological University Cork Ireland

The industry sector has the second largest energy demand after electricity generation. Given the high trend of energy prices, scarcity of its supply due to political instability and dependency on fossil fuels for its production makes energy the primary challenge for the manufacturing sector to stay competitive. Therefore, in addition to novel equipment technologies that use less energy, energy-efficient scheduling has also been a priority for manufacturing companies. In this study, the Hybrid Flowshop Scheduling Problem with Blocking Constraints and Sequence-Depend Setup Times (BHFS-SDST) is investigated for the minimization of makespan and total energy consumption (TEC). First, a novel bi-objective mixed integer linear programming (MILP) model is formulated and solved through augmented epsilon constraints. Then, a novel multi-objective approach based on Iterated Greedy meta-heuristic is developed for larger instances. Efficiency and the scalability of the proposed approaches are tested with small, medium, and large instances. Computational experiments show the effectiveness of developed methods in solving the BHFS-SDST problem.

关键词： Hybrid flowshop blocking constraint Sequence-depend setup times Makespan Energy consumption mixed integer linear programming Iterated greedy

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Comparative Network Reconstruction using mixed integer programming

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BIOINFORMATICS 2018年第17期34卷 997-1004页

作者： Bosdriesz, Evert Prahallad, Anirudh Klinger, Bertram Sieber, Anja Bosma, Astrid Bernards, Rene Bluethgen, Nils Wessels, Lodewyk F. A. Netherlands Canc Inst Oncode Inst Div Mol Carcinogenesis Amsterdam Netherlands Charite Univ Med Berlin Inst Pathol Berlin Germany Humboldt Univ IRI Life Sci Berlin Germany Berlin Inst Hlth Berlin Germany Delft Univ Technol Fac EEMCS Delft Netherlands

Motivation: Signal-transduction networks are often aberrated in cancer cells, and new anti-cancer drugs that specifically target oncogenes involved in signaling show great clinical promise. However, the effectiveness of such targeted treatments is often hampered by innate or acquired resistance due to feedbacks, crosstalks or network adaptations in response to drug treatment. A quantitative understanding of these signaling networks and how they differ between cells with different oncogenic mutations or between sensitive and resistant cells can help in addressing this problem. Results: Here, we present Comparative Network Reconstruction (CNR), a computational method to reconstruct signaling networks based on possibly incomplete perturbation data, and to identify which edges differ quantitatively between two or more signaling networks. Prior knowledge about network topology is not required but can straightforwardly be incorporated. We extensively tested our approach using simulated data and applied it to perturbation data from a BRAF mutant, PTPN11 KO cell line that developed resistance to BRAF inhibition. Comparing the reconstructed networks of sensitive and resistant cells suggests that the resistance mechanism involves reestablishing wild-type MAPK signaling, possibly through an alternative RAF-isoform.

关键词： COMPARATIVE studies mixed integer linear programming CELLULAR signal transduction CANCER cells ONCOGENES

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A Multi-Agent System Framework for Managing Distributed Energy Resources (DERs)

A Multi-Agent System Framework for Managing Distributed Ener...

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IEEE Electrical Energy Storage Application and Technologies Conference (EESAT)

作者： Omid Ziaee Beth Crouchet Chris DeBenedicts Budderfly Inc. Shelton CT USA

ISBN: (数字)9798331524852

ISBN: (纸本)9798331536411

In this paper, we propose a multi-tiered framework for controlling distributed energy resources (DERs) such as elastic and non-elastic loads, electric vehicles (EV s), and Battery Energy Storage Systems (BESS). These resources are organized into clusters. By distributing the control algorithm across these tiers, DERs optimize local operations and enhance system resilience. Local agents (LIAs) at the lowest tier optimize individual units. Cluster agents (CI As) at the second-tier aggregate cluster loads. The orchestrator agent (01 A) at the highest tier communicates with utilities or ISO/TSOs. Each LI A periodically solves a stochastic mixed-integer linear programming (MILP) problem to minimize costs and flatten the load profile. LI A results are aggregated by CI As to calculate flexible capacities. The 01 A aggregates this data to identify operational violations with the network operator, distributing necessary corrections among clusters.

关键词： Fault tolerance Costs Uncertainty Electric vehicles Scheduling Distributed power generation mixed integer linear programming Distributed algorithms Multi-agent systems Meteorology

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Optimization of Battery Energy Storage Systems for Energy Markets and Future Energy Communities

Optimization of Battery Energy Storage Systems for Energy Ma...

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International Conference on Green Energy and Applications (ICGEA)

作者： Augustin Marie Thibaut Gillot Francesco Grimaccia Sonia Leva Department of Energy Politecnico di Milano Milan Italy

ISBN: (数字)9798331530778

ISBN: (纸本)9798331530785

The increasing integration of Renewable Energy Sources (RES) into electrical grids presents also challenges related to grid stability and market dynamics. Battery Energy Storage Systems (BESS) have emerged as a potential solution to these challenges, offering capabilities for energy storage and support services that enhance grid reliability. This paper explores the optimization of the operations of such components with a case study in the Italian electricity market context. The research employs a mixed-integer linear programming (MILP) model to optimize the participation of BESS in the Day-ahead market, under the specific regulatory framework of a stock martket tender. By analyzing historical data and simulating BESS operations, this study identifies proper strategies to maximize economic returns and enhance the competitive positioning of storage systems in a specific European market context.

关键词： Green energy Fluctuations Battery energy storage system Europe Power system stability Stability analysis Real-time systems mixed integer linear programming Stock markets Optimization

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DC State Estimation Model-Based mixed integer Semidefinite programming for Optimal PMU Placement

DC State Estimation Model-Based Mixed Integer Semidefinite P...

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North American Power Symposium (NAPS)

作者： Almunif, Anas Fan, Lingling Univ S Florida Dept Elect Engn Tampa FL 33620 USA

ISBN: (纸本)9781538671382

Phasor measurement units (PMUs) can make state estimation more accurate by providing synchronized voltage phasor and current phasor measurements. Optimal PMU placement (OPP) minimizes the number of PMUs required for the system to be completely observable. This paper presents a DC state estimation model using mixed integer semidefinite programming (MISDP) approach for the OPP problem. A comparison between MISDP and mixed integer linear programming (MILP) is conducted. Power flow measurements, injection measurements, limited communication facility, and single PMU failure are studied for each approach. A formulation for MISDP-based PMU placement considering a single PMU failure is proposed. The advantages and disadvantages of each formulation are discussed.

关键词： mixed integer linear programming mixed integer semidefinite programming optimal PMU placement

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An MILP Approach for Modeling and Analyzing the BESS for Smoothing Renewable Fluctuations Considering BESS Capacity Attenuation in the Bulk Power System With High Inverter-Based Resource Penetration

An MILP Approach for Modeling and Analyzing the BESS for Smo...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Hualong Liu Wenyuan Tang Department of Electrical and Computer Engineering North Carolina State University Raleigh USA

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

Analyzing the effectiveness of the battery energy storage system (BESS) in smoothing renewable fluctuations correctly is vital to the stable operation of the power system. Therefore, based on stochastic programming and attention-based time series forecasting with learnable and interpretable basis (BasisFormer), we propose a mixed integer linear programming (MILP) approach for modeling the BESS and analyzing the effectiveness of the BESS in smoothing renewable fluctuations in the bulk power system with high inverter-based resources. The approach considers the attenuation of BESS capacity and the uncertainty of renewable generation. First, we present a scenario generation and reduction method based on Latin hypercube sampling (LHS) and the Kantorovich distance. Second, we propose a state of health (SoH) prediction method of the BESS based on BasisFormer. Third, we propose an MILP approach for modeling the BESS and analyzing the effectiveness of the BESS in smoothing renewable fluctuations. Finally, we verify the proposed approach through case studies. The experimental results show that the attenuation of BESS capacity is a crucial factor in correctly analyzing the effectiveness of the BESS in smoothing renewable fluctuations.

关键词： Renewable energy sources Analytical models Fluctuations Smoothing methods Uncertainty Battery energy storage system Attenuation Power systems mixed integer linear programming Scenario generation

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