Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms

Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events that can be non-exponentially distributed. Within parametric ACTMCs, the parameters of alarm-event distributions are not given explicitly and can be subject of parameter synthesis. An algorithm solving the $\varepsilon$-optimal parameter synthesis problem for parametric ACTMCs with long-run average optimization objectives is presented. Our approach is based on reduction of the problem to finding long-run average optimal strategies in semi-Markov decision processes (semi-MDPs) and sufficient discretization of parameter (i.e., action) space. Since the set of actions in the discretized semi-MDP can be very large, a straightforward approach based on explicit action-space construction fails to solve even simple instances of the problem. The presented algorithm uses an enhanced policy iteration on symbolic representations of the action space. The soundness of the algorithm is established for parametric ACTMCs with alarm-event distributions satisfying four mild assumptions that are shown to hold for uniform, Dirac and Weibull distributions in particular, but are satisfied for many other distributions as well. An experimental implementation shows that the symbolic technique substantially improves the efficiency of the synthesis algorithm and allows to solve instances of realistic size.Comment: This article is a full version of a paper accepted to the Conference on Quantitative Evaluation of SysTems (QEST) 201

Topics in perturbation analysis for stochastic hybrid systems

Control and optimization of Stochastic Hybrid Systems (SHS) constitute increasingly active fields of research. However, the size and complexity of SHS frequently render the use of exhaustive verification techniques prohibitive. In this context, Perturbation Analysis techniques, and in particular Infinitesimal Perturbation Analysis (IPA), have proven to be particularly useful for this class of systems. This work focuses on applying IPA to two different problems: Traffic Light Control (TLC) and control of cancer progression, both of which are viewed as dynamic optimization problems in an SHS environment. The first part of this thesis addresses the TLC problem for a single intersection modeled as a SHS. A quasi-dynamic control policy is proposed based on partial state information defined by detecting whether vehicle backlogs are above or below certain controllable threshold values. At first, the threshold parameters are controlled while assuming fixed cycle lengths and online gradient estimates of a cost metric with respect to these controllable parameters are derived using IPA techniques. These estimators are subsequently used to iteratively adjust the threshold values so as to improve overall system performance. This quasi-dynamic analysis of the TLC\ problem is subsequently extended to parameterize the control policy by green and red cycle lengths as well as queue content thresholds. IPA estimators necessary to simultaneously control the light cycles and thresholds are rederived and thereafter incorporated into a standard gradient based scheme in order to further ameliorate system performance. In the second part of this thesis, the problem of controlling cancer progression is formulated within a Stochastic Hybrid Automaton (SHA) framework. Leveraging the fact that cell-biologic changes necessary for cancer development may be schematized as a series of discrete steps, an integrative closed-loop framework is proposed for describing the progressive development of cancer and determining optimal personalized therapies. First, the problem of cancer heterogeneity is addressed through a novel Mixed Integer Linear Programming (MILP) formulation that integrates somatic mutation and gene expression data to infer the temporal sequence of events from cross-sectional data. This formulation is tested using both simulated data and real breast cancer data with matched somatic mutation and gene expression measurements from The Cancer Genome Atlas (TCGA). Second, the use of basic IPA techniques for optimal personalized cancer therapy design is introduced and a methodology applicable to stochastic models of cancer progression is developed. A case study of optimal therapy design for advanced prostate cancer is performed. Given the importance of accurate modeling in conjunction with optimal therapy design, an ensuing analysis is performed in which sensitivity estimates with respect to several model parameters are evaluated and critical parameters are identified. Finally, the tradeoff between system optimality and robustness (or, equivalently, fragility) is explored so as to generate valuable insights on modeling and control of cancer progression

Thin Games with Symmetry and Concurrent Hyland-Ong Games

We build a cartesian closed category, called Cho, based on event structures. It allows an interpretation of higher-order stateful concurrent programs that is refined and precise: on the one hand it is conservative with respect to standard Hyland-Ong games when interpreting purely functional programs as innocent strategies, while on the other hand it is much more expressive. The interpretation of programs constructs compositionally a representation of their execution that exhibits causal dependencies and remembers the points of non-deterministic branching.The construction is in two stages. First, we build a compact closed category Tcg. It is a variant of Rideau and Winskel's category CG, with the difference that games and strategies in Tcg are equipped with symmetry to express that certain events are essentially the same. This is analogous to the underlying category of AJM games enriching simple games with an equivalence relations on plays. Building on this category, we construct the cartesian closed category Cho as having as objects the standard arenas of Hyland-Ong games, with strategies, represented by certain events structures, playing on games with symmetry obtained as expanded forms of these arenas.To illustrate and give an operational light on these constructions, we interpret (a close variant of) Idealized Parallel Algol in Cho

PEMODELAN INTALASI PENGOLAHAN AIR BERSIH MENGGUNAKAN HYBRID PETRI NET

Unit instalasi pengolahan air memegang peranan penting bagi Perusahaan Daerah Air Minum (PDAM) untuk dapat menghasilkan air bersih bagi konsumen. Kualitas air bersih yang dihasilkan dan kontinuitas ketersediaan air bersih merupakan permasalahan yang harus diatasi PDAM demi terjaminnya proses distribusi air bersih kepada konsumen. Instalasi pengolahan air tidak dapat beroperasi secara terus-menerus tanpa berhenti. Suatu waktu instalasi pengolahan air harus berhenti beroperasi untuk mengistirahatkan pompa, selain itu bak-bak pengolahan juga perlu dibersihkan secara berkala agar kualitas air bersih yang dihasilkan dapat terjamin. Sistem pengolahan air bersih merupakan sistem event diskrit yang dapat dimodelkan menggunakan Petri net. Petri net biasa menggunakan bilangan bulat positif untuk menggambarkan keadaan yang terjadi. Untuk sistem pengolahan air, selain dengan bilangan bulat positif juga diperlukan bilangan rasional positif untuk dapat merepresentasikan model dengan baik. Oleh karena itu, digunakan hybrid Petri net yang terdiri dari bagian diskrit dan bagian kontinu. Bagian diskrit yang menggunakan bilangan bulat positif untuk menyatakan keadaan digunakan untuk menggambarkan keadaan pompa. Bagian kontinu yang menggunakan bilangan rasional positif untuk menyatakan keadaan digunakan untuk menggambarkan volume yang tersedia di bak pengolahan dan volume air di bak pengolahan. Dengan menggunakan pendekatan hybrid Petri net, komponen yang ada dalam instalasi pengolahan air dapat disimulasikan untuk menentukan lamanya waktu instalasi pengolahan air beroperasi dan lamanya waktu instalasi pengolahan air berhenti beroperasi, sedemikian hingga air bersih yang dihasilkan tetap dapat memenuhi kebutuhan konsumen. Pada studi kasus dengan debit air sungai 60 liter per detik diperoleh air bersih sebanyak 4536 m3 dalam waktu 24 jam dengan lamanya waktu instalasi pengolahan air beroperasi 21 jam dan berhenti beroperasi selama 3 jam. Kemudian dengan debit air sungai 30 liter per detik diperoleh air bersih sebanyak 2592 m3 dalam waktu 24 jam dengan lamanya waktu instalasi pengolahan air beroperasi 12 jam dan berhenti beroperasi selama 12 jam

High volume conveyor sortation system analysis

The design and operation of a high volume conveyor sortation system are important due to its high cost, large footprint and critical role in the system. In this thesis, we study the characteristics of the conveyor sortation system from performance evaluation and design perspectives employing continuous modeling approaches. We present two continuous conveyor models (Delay and Stock Model and Batch on Conveyor Model) with different representation accuracy in a unified mathematical framework. Based on the Batch on Conveyor Model, we develop a fast fluid simulation methodology. We address the feasibility of implementing fluid simulation from modeling capabilities, algorithm design and simulation performance in terms of accuracy and simulation time. From a design perspective, we focus on rates determination and accumulation design in the accumulation and merge subsystem. The optimization problem is to find a minimum cost design that satisfies some predefined performance requirements under stochastic conditions. We first transform this stochastic programming problem into a deterministic nonlinear programming problem through sample path based optimization method. A gradient based method is adopted to solve the deterministic problem. Since there is no closed form for performance metric even for a deterministic input stream, we adopt continuous modeling to develop deterministic performance evaluation models and conduct sensitivity analysis on these models. We explore the prospects of using the two continuous conveyor models we presented.Ph.D.Committee Chair: Chen Zhou; Committee Member: Gunter Sharp; Committee Member: Leon F. McGinnis; Committee Member: Spiridon Reveliotis; Committee Member: Yorai Ward

Book review

INTRODUCTION TO DISCRETE EVENT SYSTEMSby Christos G. Cassandras and Stèphane Lafortune,2008, Springer Science + Business Media LLC, XXIV + 776 p.,ISBN: 978-0-387-33332-8

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 22nd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 29 papers presented in this volume were carefully reviewed and selected from 85 submissions. They deal with foundational research with a clear significance for software science