mixed-integer linear programming(MILP) plays a crucial role in artificial intelligence,biochemistry,finance,cryptography,*** popular for decades,the researches of MILP solvers are still limited by the resource consump...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
mixed-integer linear programming(MILP) plays a crucial role in artificial intelligence,biochemistry,finance,cryptography,*** popular for decades,the researches of MILP solvers are still limited by the resource consumption caused by complexity and failure of Moore's ***-inspired Ising machines,as a new computing paradigm,can be used to solve integerprogramming problems by reducing them into Ising ***,it is necessary to understand the technical evolution of quantum inspired solvers to break the *** this paper,the concept and traditional algorithms for MILP are ***,focused on Ising model,the principle and implementations of annealers and coherent Ising machines are ***,the paper discusses the challenges and opportunities of miniaturized solvers in the future.
In recent years, the energy industry has increased the proportion of renewable energy sources, which are sustainable and carbon-free. However, the increase in renewable energy sources has led to grid instability due t...
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In recent years, the energy industry has increased the proportion of renewable energy sources, which are sustainable and carbon-free. However, the increase in renewable energy sources has led to grid instability due to factors such as the intermittent power generation of renewable sources, forecasting inaccuracies, and the lack of metering for small-scale power sources. Various studies have been carried out to address these issues. Among these, research on Virtual Power Plants (VPP) has focused on integrating unmanaged renewable energy sources into a unified system to improve their visibility. This research is now being applied in the energy trading market. However, the purpose of VPP aggregators has been to maximize profits. As a result, they have not considered the impact on distribution networks and have bid all available distributed resources into the energy market. While this approach has increased the visibility of renewables, an additional method is needed to deal with the grid instability caused by the increase in renewables. Consequently, grid operators have tried to address these issues by diversifying the energy market. As regulatory method, they have introduced real-time energy markets, imbalance penalty fees, and limitations on the output of distributed energy resources (DERs), in addition to the existing day-ahead market. In response, this paper proposes an optimal scheduling method for VPP aggregators that adapts to the diversifying energy market and enhances the operational benefits of VPPs by using two mixed-integer linear programming (MILP) models. The validity of the proposed model and algorithm is verified through a case study analysis.
The work undertaken in this paper pertains to the optimal spatial configuration of a heterogeneous Wireless Sensor Network (WSN) for the Area Coverage (AC) problem. Specifically, this research falls under the heading ...
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The work undertaken in this paper pertains to the optimal spatial configuration of a heterogeneous Wireless Sensor Network (WSN) for the Area Coverage (AC) problem. Specifically, this research falls under the heading of Anti -Submarine Warfare (ASW) with an emphasis on active sonar systems and, more pointedly still, on a specific type of sensor: sonobuoys (portmanteau word formed by "sonar"and "buoy"). These buoys are further divided into three main categories: transmitter-only (Tx), receiver-only (Rx) and transmitter-receiver (TxRx). In this paper, we will therefore try to determine the geographical location of the different buoys comprising a Multistatic Sonar Network (MSN), special case of WSN, so as to maximize the overall surface area covered. To do this, we discretize an Area of Interest (AoI) into regular cells using bathymetric and altimetric data, and place a deployment position and a fictitious target at the center of each cell so that we can evaluate the network's performance. More precisely, we are taking into account a limited number of sensors (buoys) with possible pairwise incompatibilities, variable performances, probabilistic detection models, an adverse masking effect (direct blast) as well as coastlines features. Finally, in order to solve this problem, we have developed several efficient mixed-integerlinear Programs (MILPs), all of which have been thoroughly tried-and-tested on a benchmark set of 100 instances derived from real elevation data. This has led us to identify an ideal model, i.e. one that is significantly better than all the others in the statistical sense.
We describe a simple method to test if a given matrix is copositive by solving a single mixed-integer linear programming (MILP) problem. This methodology requires no special coding to implement and takes advantage of ...
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We describe a simple method to test if a given matrix is copositive by solving a single mixed-integer linear programming (MILP) problem. This methodology requires no special coding to implement and takes advantage of the computational power of modern MILP solvers. Numerical experiments demonstrate that the method is robust and efficient. (C) 2020 Elsevier Inc. All rights reserved.
In oversaturated urban rail transit systems, passengers departing from downstream stations often experience long waiting times due to unbalanced space-time demand and limited transit capacity. This is often prevalent ...
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In oversaturated urban rail transit systems, passengers departing from downstream stations often experience long waiting times due to unbalanced space-time demand and limited transit capacity. This is often prevalent during morning and evening peak periods in transit systems. This paper aims to mitigate the unfairness of waiting time among a time-varying number of passengers through train timetable's adjustment by optimizing the train skip-stopping pattern. We develop an approximate general model by clustering passengers into groups and introducing an aggregation granularity parameter. To characterize feasible passenger travel patterns, both rigid first-in-first-out rule and capacity constraints are incorporated in the proposed model. Preprocessing is proposed to reduce the space of solutions. Some small-scale case studies show that the proposed method outperforms the original timetable and the preprocessing is effective to reduce computation time. Case studies based on the Batong line of Beijing rail transit network are conducted, in which a variable neighborhood search algorithm is applied to obtain high-quality solutions in short computing times. The results show that the proposed approach not only mitigates the unfairness of waiting time among passengers but also improves other efficiency evaluation indexes, including the average waiting time and the maximum number of missed trains. We also investigate the impact of the aggregation granularity parameter on the computational effort and solution accuracy. (C) 2021 Elsevier Ltd. All rights reserved.
We introduce a new facility layout problem, the so-called T-Row Facility Layout Problem (TRFLP). The TRFLP consists of a set of one-dimensional departments with pairwise transport weights between them and two orthogon...
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We introduce a new facility layout problem, the so-called T-Row Facility Layout Problem (TRFLP). The TRFLP consists of a set of one-dimensional departments with pairwise transport weights between them and two orthogonal rows which form a T such that departments in different rows cannot overlap. The aim is to find a non-overlapping assignment of the departments to the rows such that the sum of the weighted center-to-center distances measured in rectilinear directions is minimized. The TRFLP is a generalization of the well-known Multi-Bay Facility Layout Problem with three rows (3-BFLP). Both problems, the TRFLP and the 3-BFLP, have wide applications, e.g., factory planning, semiconductor fabrication and arranging rooms in hospitals. In this work we present a mixed-integer linear programming approach for the TRFLP and the 3-BFLP based on an extension of the well-known betweenness variables which now can be equal to one if the corresponding departments lie in different rows. One advantage of our formulation is the calculation of inter-row distances without big-M-type constraints. We provide cutting planes exploiting the crossroad structure in the layout, and hence T-row (3-Bay) instances with up to 18 (17) departments are solved to optimality in less than 7 h. The best known approach for the 3-BFLP is clearly outperformed. Additionally, tight lower bounds for larger instances are calculated to evaluate our heuristically determined layouts. (c) 2021 Elsevier B.V. All rights reserved.
This note is concerned with the problem of crossing a target set between sample instants under the influence of bounded unknown disturbances. The proposed solution employs mixed-integer linear programming and is less ...
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This note is concerned with the problem of crossing a target set between sample instants under the influence of bounded unknown disturbances. The proposed solution employs mixed-integer linear programming and is less conservative compared with the standard approach of imposing pointwise-in-time constraints at the sample instants.
Real-time indoor positioning systems in manufacturing systems are used to track production orders. This generates spatio-temporal trajectories which can be segmented to determine process times. We present formulations...
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The concept of transportation electrification is proliferating due to its high impact on emission reduction. However, the increased usage of electric vehicles strains the power grid's charging infrastructure. As a...
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The concept of transportation electrification is proliferating due to its high impact on emission reduction. However, the increased usage of electric vehicles strains the power grid's charging infrastructure. As a result, to reduce demand on the power grid, lower the emissions, and solve the intermittency problem of Renewable Energy Sources (RESs), a Nuclear-renewable Hybrid Energy System (N-R HES) is proposed in this research to support the load demand of a Fast Charging Station (FCS). Fulfilling the power demand of the FCS while reducing the generation cost and waste of energy is a vital issue, and hence, energy management with optimization is a must for the hybrid energy system. To address this issue, a model reference adaptive control with a mixed-integer linear programming-based energy management method was modelled to accomplish the charging station's extensive performance. MATLAB/Simulink software has been used to model and simulate the proposed system, and the results are analyzed. The assessment shows that the proposed energy management system offers an optimized performance of the fast charging station integrating with nuclear and renewable energy.
Multi-objective optimization problems (MOOP) reflect the complexity of many real-world decision problems where objectives are conflicting. The presence of more than one criterion makes finding the non-dominated (ND) p...
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Multi-objective optimization problems (MOOP) reflect the complexity of many real-world decision problems where objectives are conflicting. The presence of more than one criterion makes finding the non-dominated (ND) points a crucial issue in the decision making process. Tri-objective mixed-integerlinear programs (TOMILP) are an important subclass of MOOPs that are applicable to many problems in economics, business, science, and engineering including sustainable systems that must consider economic, environmental, and social concerns simultaneously. The literature on finding the ND points of TOMILPs is limited;there are only a few algorithms published in the literature that do not guarantee generating the entire ND points of TOMILPs. We present a new method, the Slicing with Adaptive Steps Search (SASS), to generate the ND points of TOMILPs. The result of SASS is primarily a superset of the set of ND points in the form of (partially) ND faces. We then perform a post-processing to eliminate the dominated parts of the partially ND faces. We provide a theoretical analysis of SASS and illustrate its effectiveness on a large set of instances.
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