Optimization and Engineering最新文献_第4页

Integrated batch production planning and scheduling optimization considering processing time uncertainty 考虑加工时间不确定性的综合批量生产计划和排产优化

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-04-22 DOI: 10.1007/s11081-024-09886-4

Jingxing Gao, Ziqing Guo, Linlin Liu, Yachao Dong, Jian Du

引用次数: 0

Generalized measure Black–Scholes equation: towards option self-similar pricing 广义计量布莱克-斯科尔斯方程：走向期权自相似定价

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-04-05 DOI: 10.1007/s11081-024-09885-5

Nizar Riane, Claire David

引用次数: 0

Direct and inverse problems of fractional Sturm–Liouville equation 分数 Sturm-Liouville 方程的直接和逆问题

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-25 DOI: 10.1007/s11081-024-09881-9

Zahra Kavousi Kalashmi, Hanif Mirzaei, Kazem Ghanbari

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An ensemble of artificial neural network models to forecast hourly energy demand 预测每小时能源需求的人工神经网络模型组合

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-25 DOI: 10.1007/s11081-024-09883-7

{"title":"An ensemble of artificial neural network models to forecast hourly energy demand","authors":"","doi":"10.1007/s11081-024-09883-7","DOIUrl":"https://doi.org/10.1007/s11081-024-09883-7","url":null,"abstract":"<h3>Abstract</h3> We propose an ensemble artificial neural network (EANN) methodology for predicting the day ahead energy demand of a district heating operator (DHO). Specifically, at the end of one day, we forecast the energy demand for each of the 24 h of the next day. Our methodology combines three artificial neural network (ANN) models, each capturing a different aspect of the predicted time series. In particular, the outcomes of the three ANN models are combined into a single forecast. This is done using a sequential ordered optimization procedure that establishes the weights of three models in the final output. We validate our EANN methodology using data obtained from a A2A, which is one of the major DHOs in Italy. The data pertains to a major metropolitan area in Northern Italy. We compared the performance of our EANN with the method currently used by the DHO, which is based on multiple linear regression requiring expert intervention. Furthermore, we compared our EANN with the state-of-the-art seasonal autoregressive integrated moving average and Echo State Network models. The results show that our EANN achieves better performance than the other three methods, both in terms of mean absolute percentage error (MAPE) and maximum absolute percentage error. Moreover, we demonstrate that the EANN produces good quality results for longer forecasting horizons. Finally, we note that the EANN is characterised by simplicity, as it requires little tuning of a handful of parameters. This simplicity facilitates its replicability in other cases. ","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140300675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simple and effective meta relational learning for few-shot knowledge graph completion 用于完成少量知识图谱的简单有效的元关系学习

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-25 DOI: 10.1007/s11081-024-09880-w

Shujian Chen, Bin Yang, Chenxing Zhao

{"title":"Simple and effective meta relational learning for few-shot knowledge graph completion","authors":"Shujian Chen, Bin Yang, Chenxing Zhao","doi":"10.1007/s11081-024-09880-w","DOIUrl":"https://doi.org/10.1007/s11081-024-09880-w","url":null,"abstract":"Conventional knowledge graph completion methods are effective for completing knowledge graphs (KGs), but they face significant challenges when dealing with relations with only a limited number of associative triples. To address the issue of incompleteness and long-tail distribution of relations in KGs, few-shot knowledge graph completion emerges as a promising solution. This approach predicts new triplets about a relation by leveraging only a handful of associated triples. Previous methods have focused on aggregating neighbor information and imposing sequential dependency assumptions. However, these methods can be counterproductive when they involve unrelated neighbors and rely on unrealistic assumptions, which hinders the learning of meta-representations. This paper proposes a simple and effective meta relational learning model (SMetaR) for few-shot knowledge graph completion that maintains the complete feature information of few-shot relations through a linear model. This approach effectively learns the meta-representation of few-shot relations and enhances meta-relational learning capabilities. Extensive experiments on two public datasets reveal that the model outperforms existing few-shot knowledge graph completion methods, demonstrating its effectiveness.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140300749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Service-oriented operational decision optimization for dry bulk shipping fleet under stochastic demand 随机需求下以服务为导向的干散货船队运营决策优化

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-22 DOI: 10.1007/s11081-024-09884-6

引用次数: 0

Regularized dynamics for monotone inverse variational inequalities in hilbert spaces 希尔伯特空间中单调逆变不等式的正规化动力学

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-18 DOI: 10.1007/s11081-024-09882-8

Pham Ky Anh, Trinh Ngoc Hai

引用次数: 0

Optimizing ventilation in medium- and short-term mine planning 中短期矿山规划中的通风优化

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-03-09 DOI: 10.1007/s11081-023-09871-3

John Ayaburi, Aaron Swift, Andrea Brickey, Alexandra Newman, Daniel Bienstock

{"title":"Optimizing ventilation in medium- and short-term mine planning","authors":"John Ayaburi, Aaron Swift, Andrea Brickey, Alexandra Newman, Daniel Bienstock","doi":"10.1007/s11081-023-09871-3","DOIUrl":"https://doi.org/10.1007/s11081-023-09871-3","url":null,"abstract":"Mine planners utilize production schedules to determine when activities should be executed, e.g., blocks of ore should be extracted; a medium-term schedule maximizes net present value associated with activity execution while a short-term schedule reacts to unforeseen events. Both types of schedules conform to spatial precedence and resource restrictions. As a result of executing activities, heat accumulates and activities must be curtailed. Airflow flushes heat from the mining areas, but is limited to the capacity of the ventilation system and operational setup. We propose two large-scale production scheduling models: (i) that which prescribes the start dates of activities in a medium-term schedule while considering airspeed, in conjunction with ventilation and refrigeration; and, (ii) that which minimizes deviation between both medium- and short-term schedules, and production goals. We correspondingly present novel techniques to improve model tractability, and demonstrate the efficacy of these techniques on cases that yield short-term schedules congruent with medium-term plans while ensuring the safety of the work environment. We solve otherwise-intractable medium-term instances using an enumeration technique if the gaps are greater than 10%. Our short-term instances solve in 1,800 seconds, on average, to a 0.1% optimality gap, and suggest varying optimal airspeeds based on the maximum heat load on each level.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140100126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Co-optimizing the smart grid and electric public transit bus system 共同优化智能电网和电动公交巴士系统

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-02-28 DOI: 10.1007/s11081-023-09878-w

Mertcan Yetkin, Brandon Augustino, Alberto J. Lamadrid, Lawrence V. Snyder

{"title":"Co-optimizing the smart grid and electric public transit bus system","authors":"Mertcan Yetkin, Brandon Augustino, Alberto J. Lamadrid, Lawrence V. Snyder","doi":"10.1007/s11081-023-09878-w","DOIUrl":"https://doi.org/10.1007/s11081-023-09878-w","url":null,"abstract":"As climate change provides impetus for investing in smart cities, with electrified public transit systems, we consider electric public transportation buses in an urban area, which play a role in the power system operations in addition to their typical function of serving public transit demand. Our model considers a social planner, such that the transit authority and the operator of the electricity system co-optimize the power system to minimize the total operational cost of the grid, while satisfying additional transportation constraints on buses. We provide deterministic and stochastic formulations to co-optimize the system. Each stochastic formulation provides a different set of recourse actions to manage the variable renewable energy uncertainty: ramping up/down of the conventional generators, or charging/discharging of the transit fleet. We demonstrate the capabilities of the model and the benefit obtained via a coordinated strategy. We compare the efficacies of these recourse actions to provide additional managerial insights. We analyze the effect of different pricing strategies on the co-optimization. Noting the stress growing electrified fleets with greater battery capacities will eventually impose on a power network, we provide theoretical insights on coupled investment strategies for expansion planning in order to reduce greenhouse gas (GH) emissions. Given the recent momentum towards building smarter cities and electrifying transit systems, our results provide policy directions towards a sustainable future. We test our models using modified MATPOWER case files and verify our results with different sized power networks. This study is motivated by a project with a large transit authority in California.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140887864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linewalker: line search for black box derivative-free optimization and surrogate model construction Linewalker：用于黑盒无衍生优化和代用模型构建的线性搜索

IF 2.1 3区工程技术

Optimization and Engineering Pub Date : 2024-02-21 DOI: 10.1007/s11081-023-09879-9

Dimitri J. Papageorgiou, Jan Kronqvist, Krishnan Kumaran

{"title":"Linewalker: line search for black box derivative-free optimization and surrogate model construction","authors":"Dimitri J. Papageorgiou, Jan Kronqvist, Krishnan Kumaran","doi":"10.1007/s11081-023-09879-9","DOIUrl":"https://doi.org/10.1007/s11081-023-09879-9","url":null,"abstract":"This paper describes a simple, but effective sampling method for optimizing and learning a discrete approximation (or surrogate) of a multi-dimensional function along a one-dimensional line segment of interest. The method does not rely on derivative information and the function to be learned can be a computationally-expensive “black box” function that must be queried via simulation or other means. It is assumed that the underlying function is noise-free and smooth, although the algorithm can still be effective when the underlying function is piecewise smooth. The method constructs a smooth surrogate on a set of equally-spaced grid points by evaluating the true function at a sparse set of judiciously chosen grid points. At each iteration, the surrogate’s non-tabu local minima and maxima are identified as candidates for sampling. Tabu search constructs are also used to promote diversification. If no non-tabu extrema are identified, a simple exploration step is taken by sampling the midpoint of the largest unexplored interval. The algorithm continues until a user-defined function evaluation limit is reached. Numerous examples are shown to illustrate the algorithm’s efficacy and superiority relative to state-of-the-art methods, including Bayesian optimization and NOMAD, on primarily nonconvex test functions.","PeriodicalId":56141,"journal":{"name":"Optimization and Engineering","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0