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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 3 • Date May 2009

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Displaying Results 1 - 22 of 22
  • Table of contents

    Publication Year: 2009 , Page(s): C1 - 485
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans publication information

    Publication Year: 2009 , Page(s): C2
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    Freely Available from IEEE
  • A New Efficiency-Weighted Strategy for Continuous Human/Robot Cooperation in Navigation

    Publication Year: 2009 , Page(s): 486 - 500
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1584 KB) |  | HTML iconHTML  

    Autonomous robots are capable of navigating on their own. Shared control approaches, however, allow humans to make some navigation decisions. This is typically executed either by overriding the human or the robot control at some specific situations. In this paper, we propose a method to allow cooperation between humans and robots at each point of any given trajectory so that both have some weight in the emergent behavior of the mobile robot. This is achieved by evaluating their efficiencies at each time instant and combining their commands into a single order. In order to achieve a seamless combination, this procedure is integrated into a bottom-up architecture via a reactive layer. We have tested the proposed method using a real robot and several volunteers, and results have been satisfactory both from a quantitative and qualitative point of view. View full abstract»

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  • Algebra of Systems: A Metalanguage for Model Synthesis and Evaluation

    Publication Year: 2009 , Page(s): 501 - 513
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (936 KB) |  | HTML iconHTML  

    This paper represents system models as algebraic entities and formulates model transformation activities as algebraic operations. We call this modeling framework ldquoalgebra of systemsrdquo (AoS). To show that AoS can automate complex model reasoning tasks in system design projects, we implemented the abstract algebraic specification as an executable metalanguage named object-process network, which serves as a tool for automatic model transformation, enumeration, and evaluation. A case study of the Apollo lunar landing mission design is developed using this algebraic modeling approach. View full abstract»

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  • A Generic P/T Net Model and Framework for Concurrent Integrated Design and Planning of Electromechanical Assemblies

    Publication Year: 2009 , Page(s): 514 - 527
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1252 KB) |  | HTML iconHTML  

    This paper describes a new unified formal modeling framework based on generic place/transition nets (PTNs) for concurrent integrated design and planning of electromechanical assemblies. First, a generic PTN model is defined as an abstract (meta)class of all types of PTNs. Then, an integrated object modeling framework is proposed for capturing and representing information and knowledge in the assembly design and planning processes based on the defined generic PTN modeling language and formalisms. The proposed integrated assembly model with the generic PTNs can uniformly represent the causal relations at the assembly level, the operation level, and the feature-based single-part level through the data abstraction of components and connectors on various levels of integrated assembly design and planning. An assembly model compatible with the STandard for the Exchange of Product model data (STEP, officially ISO 10303) is also built with the generic PTNs. To validate the proposed modeling framework, a prototype system has been developed, and a case study on gearbox assembly design and planning is provided. View full abstract»

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  • Determination and Management of Cable Interferences Between Two 6-DOF Foot Platforms in a Cable-Driven Locomotion Interface

    Publication Year: 2009 , Page(s): 528 - 544
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (790 KB) |  | HTML iconHTML  

    The intrinsic interaction of a robotic system that includes two 6-degree-of-freedom cable-driven platforms sharing a common workspace might result in cable interferences for random trajectories. This paper presents and analyzes computational methods for geometrically determining and managing these interferences for any trajectory constrained with variable loads. The algorithms considered determine which cable can be released from an active actuation state while allowing control in a minimal tension state, thereby ensuring that both platforms stay in a controllable workspace. The process of managing cable interferences constitutes a challenge as one must take into account the inherent limitations of the workspace, which not only include the possibility of interference itself, but also the geometry of the cable-driven locomotion interface (CDLI), its dynamics, the nonideal behavior of real cables, and the requirement that both platforms must be completely constrained at any time. As releasing a cable from an active actuation state might generate tension discontinuities in the other cables, this paper also proposes collision prediction schemes that are only applied to redundant actuators in order to reduce or completely eliminate such discontinuities. Finally, a simulation of a CDLI embedded as a peripheral in a virtual environment, in which the load applied on each platform comes from the wrench measured under the foot for a natural gait walking, is thoroughly analyzed. View full abstract»

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  • Multiattribute Choice With Ordinal Information: A Comparison of Different Decision Rules

    Publication Year: 2009 , Page(s): 545 - 554
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (757 KB) |  | HTML iconHTML  

    In the context of additive multiattribute aggregation, we address problems with ordinal information, i.e., considering a ranking of the weights (the scaling coefficients). Several rules for ranking alternatives in these situations have been proposed and compared, such as the rank-order-centroid weight, minimum value, central value, and maximum regret rules. This paper compares these rules, together with two rules that had never been studied (quasi-dominance and quasi-optimality) that use a tolerance parameter to extend the concepts of dominance and optimality. Another contribution of this paper is the study of the behavior of these rules in the context of selecting a subset of the most promising alternatives. This study intends to provide guidelines about which rules to choose and how to use them (e.g., how many alternatives to retain and what tolerance to use), considering the contradictory goals of keeping a low number of alternatives yet not excluding the best one. The comparisons are grounded on Monte Carlo simulations. View full abstract»

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  • Weighted Maximum Entropy OWA Aggregation With Applications to Decision Making Under Risk

    Publication Year: 2009 , Page(s): 555 - 564
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (196 KB) |  | HTML iconHTML  

    We introduce the basic features of the ordered weighted averaging (OWA) operator. Particular emphasis is put on the task of obtaining the associated weights. We discuss the maximal entropy OWA (MEOWA) approach to obtaining the weights. This approach is based upon the specification of a parameter characterizing the desired type of aggregation and then the solving of a mathematical programming problem whose objective is to maximize the entropy of the weights subject to this parameter. Here, we provide an alternative way of getting these MEOWA weights based upon the use of a weight-generating function. The introduction of this function allows us to obtain the MEOWA weights for the case in which each argument has a distinct degree of importance. The development of this approach allows us to use the OWA operator in decision making under risk. Here, we are able include probabilistic information as well as decision attitude to construct customized decision functions. View full abstract»

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  • An Adaptive Penalty Formulation for Constrained Evolutionary Optimization

    Publication Year: 2009 , Page(s): 565 - 578
    Cited by:  Papers (33)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (542 KB) |  | HTML iconHTML  

    This paper proposes an adaptive penalty function for solving constrained optimization problems using genetic algorithms. The proposed method aims to exploit infeasible individuals with low objective value and low constraint violation. The number of feasible individuals in the population is used to guide the search process either toward finding more feasible individuals or searching for the optimum solution. The proposed method is simple to implement and does not need any parameter tuning. The performance of the algorithm is tested on 22 benchmark functions in the literature. The results show that the proposed approach is able to find very good solutions comparable to the chosen state-of-the-art designs. Furthermore, it is able to find feasible solutions in every run for all of the benchmark functions tested. View full abstract»

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  • Multistart Tabu Search and Diversification Strategies for the Quadratic Assignment Problem

    Publication Year: 2009 , Page(s): 579 - 596
    Cited by:  Papers (38)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (642 KB) |  | HTML iconHTML  

    The quadratic assignment problem (QAP) is a well-known combinatorial optimization problem with a wide variety of applications, prominently including the facility location problem. The acknowledged difficulty of the QAP has made it the focus of many metaheuristic solution approaches. In this paper, we show the benefit of utilizing strategic diversification within the tabu search (TS) framework for the QAP, by incorporating several diversification and multistart TS variants. Computational results for an extensive and challenging set of QAP benchmark test problems demonstrate the ability of our TS variants to improve on a classic TS approach that is one of the principal and most extensively used methods for the QAP. We also show that our new procedures are highly competitive with the best recently introduced methods from the literature, including more complex hybrid approaches that incorporate the classic TS method as a subroutine. View full abstract»

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  • Ant Colony Optimization Incorporated With Fuzzy Q-Learning for Reinforcement Fuzzy Control

    Publication Year: 2009 , Page(s): 597 - 608
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (583 KB) |  | HTML iconHTML  

    This paper proposes the design of fuzzy controllers by ant colony optimization (ACO) incorporated with fuzzy-Q learning, called ACO-FQ, with reinforcements. For a fuzzy inference system, we partition the antecedent part a priori and then list all candidate consequent actions of the rules. In ACO-FQ, the tour of an ant is regarded as a combination of consequent actions selected from every rule. Searching for the best one among all combinations is partially based on pheromone trail. We assign to each candidate in the consequent part of the rule a corresponding Q-value. Update of the Q-value is based on fuzzy-Q learning. The best combination of consequent values of a fuzzy inference system is searched according to pheromone levels and Q-values. ACO-FQ is applied to three reinforcement fuzzy control problems: (1) water bath temperature control; (2) magnetic levitation control; and (3) truck backup control. Comparisons with other reinforcement fuzzy system design methods verify the performance of ACO-FQ. View full abstract»

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  • Constraint-Based Winner Determination for Auction-Based Scheduling

    Publication Year: 2009 , Page(s): 609 - 618
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (548 KB) |  | HTML iconHTML  

    This paper presents a formulation and an algorithm for the winner determination problem in auction-based scheduling. Without imposing a time line discretization, the proposed approach allows bidders to bid for the processing of a set of jobs using a requirement-based bidding language, which naturally represents scheduling constraints. The proposed winner determination algorithm uses a depth first branch and bound search. The search branches on bids, and a constraint-directed scheduling procedure is used at each node to verify the feasibility of the temporary schedule. Experiments show that the proposed algorithm is on average more than an order of magnitude faster than a commercial optimization package, CPLEX 10.0. View full abstract»

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  • Optimal Pair of Minimal Paths Under Both Time and Budget Constraints

    Publication Year: 2009 , Page(s): 619 - 625
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (238 KB) |  | HTML iconHTML  

    The quickest path (QP) problem is to find a path which sends a given amount of data from the source to the sink such that the transmission time is minimized. Two attributes are involved, namely, the capacity and the lead time. The capacity of each arc is assumed to be deterministic. However, in many real-life flow networks such as computer systems, telecommunication systems, etc., the capacity of each arc should be stochastic due to failure, maintenance, etc. Such a network is named a stochastic-flow network. Hence, the minimum transmission time is not a fixed number. We modify the QP problem to a stochastic case. The new problem is to evaluate the probability that d units of data can be sent from the source to the sink under both time T and budget B constraints. Such a probability is named the system reliability. In particular, the data can be transmitted through two disjoint minimal paths (MPs) simultaneously. A simple algorithm is proposed to generate all (d, T, B)-QPs, and the system reliability can subsequently be computed. The optimal pair of MPs with highest system reliability could further be obtained. View full abstract»

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  • Exploiting Redundancies to Enhance Schedulability in Fault-Tolerant and Real-Time Distributed Systems

    Publication Year: 2009 , Page(s): 626 - 639
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (839 KB) |  | HTML iconHTML  

    In the past decades, distributed systems have been widely applied to real-time applications, most of which have fault-tolerance requirements to assure high reliability. Due to the stringent space constraints of real-time systems, the issue of schedulability becomes a major concern in the design of fault-tolerant and real-time distributed systems. Most existing real-time and fault-tolerant scheduling algorithms, which are based on the primary-backup scheme for periodic real-time tasks, introduce unnecessary redundancies by aggressively using active-backup copies. To solve this problem, we propose two novel fault-tolerant techniques, which are seamlessly integrated with fixed-priority-based scheduling algorithms. These techniques leverage redundancies to enhance schedulability in fault-tolerant and real-time distributed systems. Our fault-tolerant techniques make use of the primary-backup scheme to tolerate permanent hardware failures. The first technique (referred to as Tercos) terminates the execution of active-backup copies, when corresponding primary copies are successfully completed. Tercos is designed to reduce scheduling lengths in fault-free scenarios to enhance schedulability by virtue of executing portions of active-backup copies in passive forms. The second technique (referred to as Debus) uses a deferred-active-backup scheme to further minimize schedule lengths to improve the schedulability performance. Debus schedules active-backup copies as late as possible, while terminating active-backup copies when their primary copies are completed. Experimental results show that, compared with existing algorithms in literature, Tercos can significantly improve schedulability by up to 17.0% (with an average of 9.7%). Furthermore, empirical results reveal that Debus can enhance schedulability over Tercos by up to 12% (with an average of 7.8%). View full abstract»

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  • Hierarchical Test Sequencing for Complex Systems

    Publication Year: 2009 , Page(s): 640 - 649
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (404 KB) |  | HTML iconHTML  

    Testing complex systems, such as the ASML TWINSCAN lithographic machine, is expensive and time consuming. In a previous work, a test sequencing method to calculate time-optimal test sequences has been developed. Because complex systems are composed of several subsystems, which are again composed of several modules, there exists a need to hierarchically model test sequencing problems. Such a hierarchical test sequencing problem consists of a high-level model that describes a test sequencing problem at the system level, and one or more low-level models that describe the test sequencing problems at the subsystem or module level. The tests at the system level correspond to the solutions of low-level problems. This paper describes a hierarchical test sequencing model and proposes two algorithms to compute an optimal test sequence. The benefits of hierarchically modeling a problem are less computational effort and less modeling effort, because not all relations are needed. This is illustrated by a small example. The industrial relevance of this method is illustrated on a case study related to a manufacturing testing phase of a lithographic machine. View full abstract»

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  • Combined Siphon and Marking Generation for Deadlock Prevention in Petri Nets

    Publication Year: 2009 , Page(s): 650 - 661
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (418 KB) |  | HTML iconHTML  

    In Petri-net (PN) modeling of flexible manufacturing systems, deadlock prevention is often addressed by means of siphon-control methods. Constraints that avoid the emptying of siphons can be easily implemented using additional places suitably connected to the PN transitions. Efficient siphon-based techniques achieve highly permissive solutions using as few control places as possible. One such technique employs a set-covering approach to optimally match emptiable siphons to critical markings. In this paper, a modified version of the method is proposed that achieves the same results in terms of permissivity and size of the control subnet but avoids full siphon enumeration. This greatly reduces the overall computational time and memory requirements and allows the applicability of the method to large-size models. View full abstract»

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  • Learning and Herding Using Case-Based Decisions With Local Interactions

    Publication Year: 2009 , Page(s): 662 - 669
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (639 KB) |  | HTML iconHTML  

    We evaluate repeated decisions of individuals using a variant of the case-based decision theory (CBDT), where individuals base their decisions on their own past experience and the experience of neighboring individuals. Looking at a range of scenarios to determine the successful outcome of a decision, we find that for learning to occur, agents must have a sufficient number of neighbors to learn from and access to sufficiently independent information. If these conditions are not fulfilled, we can easily observe herding in cases where no best decision exists. View full abstract»

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  • On Stability of the Chemotactic Dynamics in Bacterial-Foraging Optimization Algorithm

    Publication Year: 2009 , Page(s): 670 - 679
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (554 KB) |  | HTML iconHTML  

    Bacterial-foraging optimization algorithm (BFOA) attempts to model the individual and group behavior of E.Coli bacteria as a distributed optimization process. Since its inception, BFOA has been finding many important applications in real-world optimization problems from diverse domains of science and engineering. One key step in BFOA is the computational chemotaxis, where a bacterium (which models a candidate solution of the optimization problem) takes steps over the foraging landscape in order to reach regions with high-nutrient content (corresponding to higher fitness). The simulated chemotactic movement of a bacterium may be viewed as a guided random walk or a kind of stochastic hill climbing from the viewpoint of optimization theory. In this paper, we first derive a mathematical model for the chemotactic movements of an artificial bacterium living in continuous time. The stability and convergence-behavior of the said dynamics is then analyzed in the light of Lyapunov stability theorems. The analysis indicates the necessary bounds on the chemotactic step-height parameter that avoids limit cycles and guarantees convergence of the bacterial dynamics into an isolated optimum. Illustrative examples as well as simulation results have been provided in order to support the analytical treatments. View full abstract»

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  • Optimal Contraction Theorem for Exploration–Exploitation Tradeoff in Search and Optimization

    Publication Year: 2009 , Page(s): 680 - 691
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (764 KB) |  | HTML iconHTML  

    Global optimization process can often be divided into two subprocesses: exploration and exploitation. The tradeoff between exploration and exploitation (T:Er&Ei) is crucial in search and optimization, having a great effect on global optimization performance, e.g., accuracy and convergence speed of optimization algorithms. In this paper, definitions of exploration and exploitation are first given based on information correlation among samplings. Then, some general indicators of optimization hardness are presented to characterize problem difficulties. By analyzing a typical contraction-based three-stage optimization process, optimal contraction theorem is presented to show that T:Er&Ei depends on the optimization hardness of problems to be optimized. T:Er&Ei will gradually lean toward exploration as optimization hardness increases. In the case of great optimization hardness, exploration-dominated optimizers outperform exploitation-dominated optimizers. In particular, random sampling will become an outstanding optimizer when optimization hardness reaches a certain degree. Besides, the optimal number of contraction stages increases with optimization hardness. In an optimal contraction way, the whole sampling cost is evenly distributed in all contraction stages, and each contraction takes the same contracting ratio. Furthermore, the characterization of optimization hardness is discussed in detail. The experiments with several typical global optimization algorithms used to optimize three groups of test problems validate the correctness of the conclusions made by T:Er&Ei analysis. View full abstract»

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  • Comments on "An iterative synthesis approach to petri net based deadlock prevention policy for flexible manufacturing systems"

    Publication Year: 2009 , Page(s): 692
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (52 KB) |  | HTML iconHTML  

    In the above paper, it proposes a deadlock prevention policy for a flexible manufacturing system (FMS), which needs the complete state enumeration of the FMS that is modeled with Petri nets. The reachability graph of a Petri-net model is divided into two parts: the live zone (LZ) and the deadlock zone (DZ). The states in the LZ of the reachability graph of a Petri net constitute the legal behavior of the net from the viewpoint of deadlock prevention. The concept of first-met bad markings is proposed. A first-met bad marking is a node in DZ, whose father nodes are in LZ. The deadlock prevention policy is used in an iterative way. At each iteration, a first-met bad marking is identified from the reachability graph of a Petri net to be controlled. The reachability of a first-met bad marking is prohibited by adding a monitor, establishing a marking invariance relationship between the additional monitor and the activity places that are marked under the first-met bad marking. To achieve this, without a formal proof, [Lemma 1] is developed as shown in this article. View full abstract»

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  • IEEE Systems, Man, and Cybernetics Society Information

    Publication Year: 2009 , Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (29 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans Information for authors

    Publication Year: 2009 , Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (35 KB)  
    Freely Available from IEEE

Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta