Publications related to Local search (optimization)

Assisted Specification of Discrete Choice Models

Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. As the number of possible functions exponentially grows with the variables under consideration, analysts need to spend increasing amounts of ti ...

2020

Combinatorial optimization of Dedicated Bus Lane layout in urban networks with dynamic congestion

Nikolaos Geroliminis, Dimitrios Tsitsokas, Anastasios Kouvelas

Transit priority based in exclusive right-of-way is a low-cost way of improving transit service by minimizing delays caused by interaction with other vehicles. This effect can increase the share of public transit against private cars in the mode preference ...

2020

A Computational Method for Identifying the Optimum Buffer Size in the Era of Zero Defect Manufacturing

Ali Boujemaoui

Decreasing defects, waste time, meeting customer demand and being adaptable are the goals of a Zero Defect Manufacturing (ZDM) strategy. Scheduling is an important tool to perform that. It should take in account buffer size allocation. In this study, a met ...

SPRINGER INTERNATIONAL PUBLISHING AG2020

A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain

Fernando Porté Agel, Roberto Brogna

Layout optimization of wind farms constitutes an important and challenging task in complex terrain. This is especially due to the complex interactions of the boundary layer flows in complex terrain and wind turbine wakes, which renders wake modelling in co ...

ELSEVIER SCI LTD2020

Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Safe non-smooth black-box optimization with application to policy search

Maryam Kamgarpour, Andreas Krause, Ilnura Usmanova

For safety-critical black-box optimization tasks, observations of the constraints and the objective are often noisy and available only for the feasible points. We propose an approach based on log barriers to find a local solution of a non-convex non-smooth ...

PMLR2020

Design of structures that adapt to loads through large shape changes

Ian Smith, Gennaro Senatore, Arka Prabhata Reksowardojo

Adaptive structures can modify their geometry and internal forces through sensing and mechanical actuation in order to maintain optimal performance under changing actions. Previous work has shown that well-conceived adaptive design strategies achieve subst ...

2020

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Volkan Cevher, Ali Kavis, Shaul Nadav Hallak

This paper analyzes the trajectories of stochastic gradient descent (SGD) to help understand the algorithm’s convergence properties in non-convex problems. We first show that the sequence of iterates generated by SGD remains bounded and converges with prob ...

2020

Optimal target assignment for massive spectroscopic surveys

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

Robotics have recently contributed to cosmological spectroscopy to automatically obtain the map of the observable universe using robotic fiber positioners. For this purpose, an assignment algorithm is required to assign each robotic fiber positioner to a t ...

2020

Extrapolation for Large-batch Training in Deep Learning

Martin Jaggi, Sebastian Urban Stich, Tao Lin, Lingjing Kong

Deep learning networks are typically trained by Stochastic Gradient Descent (SGD) methods that iteratively improve the model parameters by estimating a gradient on a very small fraction of the training data. A major roadblock faced when increasing the batc ...

2020

Local search (optimization)

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Assisted Specification of Discrete Choice Models

Combinatorial optimization of Dedicated Bus Lane layout in urban networks with dynamic congestion

A Computational Method for Identifying the Optimum Buffer Size in the Era of Zero Defect Manufacturing

A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain

Square Attack: a query-efficient black-box adversarial attack via random search

Safe non-smooth black-box optimization with application to policy search

Design of structures that adapt to loads through large shape changes

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Optimal target assignment for massive spectroscopic surveys

Extrapolation for Large-batch Training in Deep Learning

Combinatorial optimization of Dedicated Bus Lane layout in urban networks with dynamic congestion

A Computational Method for Identifying the Optimum Buffer Size in the Era of Zero Defect Manufacturing

Assisted Specification of Discrete Choice Models

A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain

Square Attack: a query-efficient black-box adversarial attack via random search

Safe non-smooth black-box optimization with application to policy search

Design of structures that adapt to loads through large shape changes

Optimal target assignment for massive spectroscopic surveys

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems

Extrapolation for Large-batch Training in Deep Learning