Scheduling and calibration strategy for continuous radio monitoring of 1700 sources every three days

The Owens Valley Radio Observatory 40 meter telescope is currently monitoring a sample of about 1700 blazars every three days at 15 GHz, with the main scientific goal of determining the relation between the variability of blazars at radio and gamma-rays as observed with the Fermi Gamma-ray Space Telescope. The time domain relation between radio and gamma-ray emission, in particular its correlation and time lag, can help us determine the location of the high-energy emission site in blazars, a current open question in blazar research. To achieve this goal, continuous observation of a large sample of blazars in a time scale of less than a week is indispensable. Since we only look at bright targets, the time available for target observations is mostly limited by source observability, calibration requirements and slewing of the telescope. Here I describe the implementation of a practical solution to this scheduling, calibration, and slewing time minimization problem. This solution combines ideas from optimization, in particular the traveling salesman problem, with astronomical and instrumental constraints. A heuristic solution using well stablished optimization techniques and astronomical insights particular to this situation, allow us to observe all the sources in the required three days cadence while obtaining reliable calibration of the radio flux densities. Problems of this nature will only be more common in the future and the ideas presented here can be relevant for other observing programs.Comment: Published in Proc. SPIE. 9149, Observatory Operations: Strategies, Processes, and Systems V, 91492

Multi-use lunar telescopes

The objective of multi-use telescopes is to reduce the initial and operational costs of space telescopes to the point where a fair number of telescopes, a dozen or so, would be affordable. The basic approach is to develop a common telescope, control system, and power and communications subsystem that can be used with a wide variety of instrument payloads, i.e., imaging CCD cameras, photometers, spectrographs, etc. By having such a multi-use and multi-user telescope, a common practice for earth-based telescopes, development cost can be shared across many telescopes, and the telescopes can be produced in economical batches

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the ``single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes, causing the codification of this knowledge to become laborious. We propose a new approach for capturing domain-expert heuristics through a pairwise ranking formulation. Our approach is model-free and does not require enumerating or iterating through a large state space. We empirically demonstrate that this approach accurately learns multifaceted heuristics on a synthetic data set incorporating job-shop scheduling and vehicle routing problems, as well as on two real-world data sets consisting of demonstrations of experts solving a weapon-to-target assignment problem and a hospital resource allocation problem. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of a branch-and-bound search for an optimal schedule. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates solutions substantially superior to those produced by human domain experts at a rate up to 9.5 times faster than an optimization approach and can be applied to optimally solve problems twice as complex as those solved by a human demonstrator.Comment: Portions of this paper were published in the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper consists of 50 pages with 11 figures and 4 table

Dynamic threshold policy for delaying and breaking commitments in transportation auctions

In this paper we consider a transportation procurement auction consisting of shippers and carriers. Shippers offer time sensitive pickup and delivery jobs and carriers bid on these jobs. We focus on revenue maximizing strategies for shippers in sequential auctions. For this purpose we propose two strategies, namely delaying and breaking commitments. The idea of delaying commitments is that a shipper will not agree with the best bid whenever it is above a certain reserve price. The idea of breaking commitments is that the shipper allows the carriers to break commitments against certain penalties. The benefits of both strategies are evaluated with simulation. In addition we provide insight in the distribution of the lowest bid, which is estimated by the shippers

The impact of the soccer schedule on TV viewership and stadium attendance : evidence from the Belgian Pro League

In the past decade, television broadcasters have been investing a huge amount of money for the Belgian Pro League broadcasting rights. These companies pursue an audience rating maximization, which depends heavily on the schedule of the league matches. At the same time, clubs try to maximize their home attendance and find themselves affected by the schedule as well. Our paper aims to capture the Belgian soccer fans’ preferences with respect to scheduling options, both for watching matches on TV and in the stadium. We carried out a discrete choice experiment using an online survey questionnaire distributed on a national scale. The choice sets are based on three match characteristics: month, kickoff time, and quality of the opponent. The first part of this survey concerns television broadcasting aspects. The second part includes questions about stadium attendance. The choice data is first analyzed with a conditional logit model which assumes homogenous preferences. Then a mixed logit model is fit to model the heterogeneity among the fans. The estimates are used to calculate the expected utility of watching a Belgian Pro League match for every possible setting, either on TV or in the stadium. These predictions are validated in terms of the real audience rating and home attendance data. Our results can be used to improve the scheduling process of the Belgian Pro League in order to persuade more fans to watch the matches on TV or in a stadium