Journal of Industrial & Management Optimization
Open Access Articles
In this paper, we consider the new online scheduling model with linear lookahead intervals, which has the character that at any time
We present an effective hybrid metaheuristic of integrating reinforcement learning with a tabu-search (RLTS) algorithm for solving the max–mean dispersion problem. The innovative element is to design using a knowledge strategy from the
Heating, Ventilation, and Air-Condition (HVAC) systems are considered to be one of the essential applications for modern human life comfort. Due to global warming and population growth, the demand for such HVAC applications will continue to increase, especially in arid areas countries like the Arabian Gulf region. HVAC systems' energy consumption is very high and accounts for up to 70% of the total load consumption in some rapidly growing GCC countries such as Qatar. Additionally, the local extremely hot weather conditions usually lead to typical power demand peak issues that require adequate mitigation measures to ensure grid stability. In this paper, a novel control scheme for a combined group of Air-Conditioners is proposed as a peak-shaving strategy to address high power demand issues for Photo-Voltaic(PV)-integrated micro-grid applications. Using the local daily ambient temperature as input, the AC group control optimization is formulated as a Mixed-Integer Quadratic Programming (MIQP) problem. Under an acceptable range of indoor temperatures, the units in the same AC group are coordinately controlled to generate desired power consumption performance that is capable of shaving load peaks for both power consumption and PV generation. Finally, various simulations are performed that demonstrate the effectiveness of the proposed control strategy.
Considering the parameter uncertainty and actuator failure of hypersonic vehicle during maneuvering, this paper proposes a state observer-based hypersonic vehicle fault-tolerant control (FTC) system design method. Because hypersonic vehicles are prone to failure during maneuvering, the state quantity cannot be measured. First, a state observer-based FTC control method is designed for the linear parameter-varying (LPV) model with parameter uncertainty and partial failure of the actuator. Then, the Lyapunov function is used to demonstrate the asymptotic stability of the closed-loop system. The performance index function proved that the system has robust stability under the disturbance condition. Subsequently, the linear matrix inequality (LMI) was used to solve the observer parameters and the corresponding gain matrix in the control system. The simulation results indicated that the designed controller can track the flight command signal stably and has strong robustness, which verified the effectiveness of the design controller.
This paper studies a finite-sized discrete-time two-class priority queue. Packets of both classes arrive according to a two-class discrete batch Markovian arrival process (2-DBMAP), taking into account the correlated nature of arrivals in heterogeneous telecommunication networks. The model incorporates time and space priority to provide different types of service to each class. One of both classes receives absolute time priority in order to minimize its delay. Space priority is implemented by the partial buffer sharing acceptance policy and can be provided to the class receiving time priority or to the other class. This choice gives rise to two different queueing models and this paper analyses both these models in a unified manner. Furthermore, the buffer finiteness and the use of space priority raise some issues on the order of arrivals in a slot. This paper does not assume that all arrivals from one class enter the queue before those of the other class. Instead, a string representation for sequences of arriving packets and a probability measure on the set of such strings are introduced. This naturally gives rise to the notion of intra-slot space priority. Performance of these queueing systems is then determined using matrix-analytic techniques. The numerical examples explore the range of service differentiation covered by both models.
A well-known problem with priority policies is starvation of delay-tolerant traffic. Additionally, insufficient control over delay differentiation (which is needed for modern network applications) has incited the development of sophisticated scheduling disciplines. The priority policy we present here has the benefit of being open to rigorous analysis. We study a discrete-time queueing system with a single server and single queue, in which $N$ types of customers enter pertaining to different priorities. A general i.i.d. arrival process is assumed and service times are generally distributed. We divide the time axis into 'frames' of fixed size (counted as a number of time-slots), and reorder the customers that enter the system during the same frame such that the high-priority customers are served first. This paper gives an analytic approach to studying such a system, and in particular focuses on the system content (meaning the customers of each type in the system at random slotmarks) in stationary regime, and the delay distribution of a random customer. Clearly, in such a system the frame's size is the key factor in the delay differentiation between the $N$ priority classes. The numerical results at the end of this paper illustrate this observation.
This special issue is a collection of papers selected from the revised and expanded versions of papers presented at the Third Asia-Pacific Symposium on Queueing Theory and Network Applications (QTNA2008), July 30-August 2, 2008, Taipei, Taiwan.
Included are 10 papers of high quality which were selected from among those contributed papers in QTNA2008. They have all been peer-reviewed by two or more referees according to the normal standard of the journal.
The special issue aims at publishing high quality papers dealing with performance analysis and system management of communication networks and related systems.
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This special issue is devoted to showcase selected papers from the XIII CLAIO (Conferencia Latino-Ibero-Americana de Investigación Operativa, the Latin-Ibero- American Conference on Operations Research). This event is the flagship conference of ALIO, the Latin-Ibero-American Operations Research Association. The CLAIO, which is held biennially, is the main meeting point of the Latin-American Operations Research academic community. The event also fosters and features the participation of researchers from all over the world.
The papers presented in this special issue cover part of the large diversity of subjects covered at CLAIO, ranging from theoretical to applied viewpoints. Over 350 extended abstracts were accepted to the conference, providing novel methodological contributions, models, and algorithms, as well as case studies that illustrate the application of optimization in real-life settings. We are pleased to introduce here a representative set of papers, arising from our selection and the refereeing process.
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This special issue is a collection of selected papers presented at the 7th International Conference on Optimization: Techniques and Applications (ICOTA 7), which took place from December 12-15, 2007 in Kobe, Japan. ICOTA is an official conference series of POP (The Pacific Optimization Research Activity Group) and ICOTA 7 was organized by the Institute of Intelligent Information and Communications Technology (IICT) of Konan University. The purpose of this tri-annual conference is to provide a forum for international researchers and practitioners to highlight their major advances in optimization techniques and applications since ICOTA 6 held in December, 2004 in Ballarat, Australia.
Over two hundred papers were presented at ICOTA 7. The thirteen papers published in this special issue cover a wide range of topics in optimization techniques and their applications, as outlined below.
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We are very pleased to dedicate this Special Issue of the Journal of Industrial and Management Optimization to Professor Yacov Y. Haimes for his pioneering and significant contributions over forty years to various aspects of systems engineering and risk management including planning, design, management and operation of water resources, transportation and other interdependent infrastructure systems, multiple objective optimization and hierarchical analysis of large-scale systems, as a scholar and educator.
Optimization and optimal control problems arise in diverse areas such as traditional engineering, natural resource utilization, financial engineering, vehicle route selection and supply chain planning. This special issue contains eight full-length papers reflecting the recent advances in the numerical solution of some complex optimization and optimal control problems. Most of these results were orally presented in the special session entitled 'Optimization and Optimal Control with Applications' of the AIMS' 6th International Conference on Dynamical Systems, Differential Equations and Applications held at University of Poitiers, France from June 25th - 28th, 2006.
This special issue is dedicated to Professor Changyu Wang on the occasion of his 70th birthday in recognition of his contributions to Operations Research and its applications and his lasting impact as an educator.
This special issue is based on, but not limited to, contributions from invited speakers of the International Workshop in Financial Mathematics and Statistics held at the Hong Kong Polytechnic University, on December 16, 2004. The workshop was well attended by experts in the field all over the world.
The issue aims to look at leading-edge research on the interface between derivatives, insurance, securities and quantitative finance. As financial mathematics and statistics are two essential components in these four areas, the issue, as we hope, will give the readers a survey of the important tools of mathematics and statistics being used in the modern financial institutions.
In this special issue, 7 papers are included. The papers cover mathematical finance topics, such as option pricing, interest models and stochastic volatility; topics in risk management, such as Value at Risk, liquidity risk management; and actuarial science topics, such as ruin theory.
The papers in the issue were selected with a view towards readers coming from finance, actuarial science, mathematics or statistics. Hopefully this is a first step to provide a platform for people who are interested in the interplay among theory and practice of these disciplines.
This inaugural issue of JIMO is dedicated to Professor Franco Giannessi on the occasion of his 70th birthday and in recognition of his many fundamental contributions in optimization and optimal control. During his long career, through his tremendous work Professor Giannessi has influenced many researchers on their scientific activity of in the areas of optimization and optimal control. Professor Franco Giannessi has won the admiration and affection of those who know him. It fits that this special issue is dedicated to him because not only he has been a major contributor in the field but also he has long association with many members of the Editorial Board of JIMO and he always offers his support and encouragement in their career and scientific development. Professor Franco Giannessi is an outstanding scholar, and excellent colleague and friend.
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