Precedence Order Research Articles

Standby Redundancy Allocations in Series and Parallel Systems

To enhance the performance of a system, a common practice employed by reliability engineers is to use redundant components in the system. In this paper we compare lifetimes of series (parallel) systems arising out of different allocations of one or two standby redundancies. These comparisons are made with respect to the increasing concave (convex) order, the hazard rate order, and the stochastic precedence order. The main results extend some related conclusions in the literature.

전제조건과 IDEF3를 응용한 동시공학환경에서의 복합설계

Engineering design involves the specification of many variables that define a product, how it is made, and how it behaves applied to computer, communication and control fields. Before some variables can be determined, other variables must first be known or assumed. This fact implies a precedence order of the variables, and of the tasks of determining these variables consequently. Moreover, design of complex systems may involve a large number of design activities. In this paper, the activity-activity incidence matrix is considered as a representation of design activity analysis which mainly focuses on the precedence constraint with an object of doing IDEF3 in process-centered view. In order to analyze the activity-activity incidence matrix, a heuristic algorithm is proposed, which transforms an activity-activity, parameter-formula, and parameter-parameter incidence matrix into a lower triangular form. The analysis of the structured matrices can not only significantly reduce the overall project complexity by reorganizing few critical tasks in practice, but also aims at obtaining shorter times considering the solution structure by exploring concurrency.

A new polynomial algorithm for a parallel identical scheduling problem

A precedence order is defined based on the release dates of jobs’ direct successors. Using the defined precedence order and Heap Sort, a new polynomial algorithm is provided which aims to solve the parallel scheduling problem P|p j = 1, r j , outtree| Σ C j . The new algorithm is shown to be more compact and easier to implement.

Extracting constrained 2-interval subsets in 2-interval sets

2-interval sets were used in [S. Vialette, Pattern matching over 2-intervals sets, in: Proc. 13th Annual Symposium Combinatorial Pattern Matching, CPM 2002, in: Lecture Notes in Computer Science, vol. 2373, Springer-Verlag, 2002, pp. 53–63; S. Vialette, On the computational complexity of 2-interval pattern matching, Theoret. Comput. Sci. 312 (2–3) (2004) 223–249] for establishing a general representation for macroscopic describers of RNA secondary structures. In this context, we have a 2-interval for each legal local fold in a given RNA sequence, and a constrained pattern made of disjoint 2-intervals represents a putative RNA secondary structure. We focus here on the problem of extracting a constrained pattern in a set of 2-intervals. More precisely, given a set of 2-intervals D and a model R describing if two disjoint 2-intervals in a solution can be in precedence order (<), be allowed to nest ( ⊏ ) and/or be allowed to cross ( ≬ ), we consider the problem of finding a maximum cardinality subset D ′ ⊆ D of disjoint 2-intervals such that any two 2-intervals in D ′ agree with R . The different combinations of restrictions on model R alter the computational complexity of the problem, and need to be examined separately. In this paper, we improve the time complexity of [S. Vialette, On the computational complexity of 2-interval pattern matching, Theoret. Comput. Sci. 312 (2–3) (2004) 223–249] for model R = { ⊏ } by giving an optimal O ( n log n ) time algorithm, where n is the cardinality of the 2-interval set D . We also give a graph-like relaxation for model R = { ⊏ , ≬ } that is solvable in O ( n 2 n ) time. Finally, we prove that the considered problem is NP-complete for model R = { < , ≬ } even for same-length intervals, and give a fixed-parameter tractability result based on the crossing structure of D .

An Improved Augmented Neural-Network Approach for Scheduling Problems

For the task-scheduling problem, we propose an augmented neural-network approach, which allows the integration of greedy as well as nongreedy heuristics (AugNN-GNG), to give improved solutions in a small number of iterations. The problem we address is that of minimizing the makespan of n tasks on m identical machines (or processors), where tasks are nonpreemptive and follow a precedence order. The proposed approach exploits the observation that a nongreedy search heuristic often finds better solutions than do their greedy counterparts. We hypothesize that combinations of nongreedy and greedy heuristics when integrated with an augmented neural-network approach can lead to better solutions than can either one alone. We show the formulation of such integration and provide empirical results on over a thousand problems. This approach is found to be very robust in that the results were not very sensitive to the type of greedy heuristic chosen. The new approach is able to find solutions, on average, within 1.8% to 2.8% of the lower bound compared to 2.0% to 8.3% for the greedy-only AugNN approach. This improvement is obtained without any increase in computational complexity. In fact the number of iterations used to find the solution decreased.

A new heuristic for the multi-mode resource investment problem

This paper considers the problem of minimizing resource investment required to execute the tasks in a project network by a given project due date. A project consists of non-pre-emptive tasks executed in a known and required precedence order. Each task is completed in one of its feasible modes, which may differ not only in task duration but also in consumption of renewable resources. A priority rule heuristic with polynomial computational complexity is presented for this computationally intractable problem. This heuristic simultaneously considers due date constraints and resource usage to select and schedule tasks with one decision rule. This differs from prior multi-mode priority rule scheduling heuristics that apply two consecutive decision rules to schedule tasks. Extensive computational testing indicates promising results.

The stochastic precedence ordering with applications in sampling and testing

Stratified and simple random sampling (or testing) are two common methods used to investigate the number or proportion of items in a population with a particular attribute. Although it is known that cost factors and information about the strata in the population are often crucial in deciding whether to use stratified or simple random sampling in a given situation, the stochastic precedence ordering for random variables can also provide the basis for an interesting criteria under which these methods may be compared. It may be particularly relevant when we are trying to find as many special items as possible in a population (for example individuals with a disease in a country). Properties of this total stochastic order on the class of random variables are discussed, and necessary and sufficient conditions are established which allow the comparison of the number of items of interest found in stratified random sampling with the number found in simple random sampling in the stochastic precedence order. These conditions are compared with other results established on stratified and simple random sampling (testing) using different stochastic-order-type criteria, and applications are given for the comparison of sums of Bernoulli random variables and binomial distributions.

The stochastic precedence ordering with applications in sampling and testing

Stratified and simple random sampling (or testing) are two common methods used to investigate the number or proportion of items in a population with a particular attribute. Although it is known that cost factors and information about the strata in the population are often crucial in deciding whether to use stratified or simple random sampling in a given situation, the stochastic precedence ordering for random variables can also provide the basis for an interesting criteria under which these methods may be compared. It may be particularly relevant when we are trying to find as many special items as possible in a population (for example individuals with a disease in a country). Properties of this total stochastic order on the class of random variables are discussed, and necessary and sufficient conditions are established which allow the comparison of the number of items of interest found in stratified random sampling with the number found in simple random sampling in the stochastic precedence order. These conditions are compared with other results established on stratified and simple random sampling (testing) using different stochastic-order-type criteria, and applications are given for the comparison of sums of Bernoulli random variables and binomial distributions.

Asynchronous operations in distributed concurrency control

Distributed locking is commonly adopted for performing concurrency control in distributed systems. It incorporates additional steps for handling deadlocks. This activity is carried out by methods based on wait-for-graphs or probes. The present study examines detection of conflicts based on enhanced local processing for distributed concurrency control. In the proposed "edge detection" approach, a graph-based resolution of access conflicts has been adopted. The technique generates a uniform wait-for precedence order at distributed sites for transactions to execute. The earlier methods based on serialization graph testing are difficult to implement in a distributed environment. The edge detection approach is a fully distributed approach. It presents a unified technique for locking and deadlock detection exercises. The technique eliminates many deadlocks without incurring message overheads.

Fuzzy compromise programming with precedence order in the criteria

This paper provides a new multi-objective decision making (MODM) method. The method was developed by extending two known approaches: “fuzzy composite programming” and “multi-attribute decision making with dominance in the attributes”. The method allows the inclusion of a fuzzy representation of uncertainty relative to the information used through the decision making process. In this way the decision-maker is able to incorporate ambiguity and imprecision, which are common to most of the decision problems. The new methodology also addresses the ambiguity surrounding the relative importance of objectives. Thus, in the decision making process the decision-maker is not required to assign specific weights to the objectives to indicate their relative importance. Only a precedence order in the objectives becomes necessary to achieve a ranking in the alternatives. The MODM was applied to assess six management alternatives for the karstic aquifer management problem presented by previous authors. The design alternatives were evaluated against six objectives, which were grouped in three principal criteria: “Environmental”, “Economic”, and “Water Quality”. The method was also evaluated in light of existing methods. It was demonstrated that, as a distance-based method, the new methodology preserves the characteristics of fuzzy composite programming but, at the same time allows the decision-maker flexibility in the assignment of relative importance between objectives.

Subset-Restricted Interchange for Dynamic Min-Max Scheduling Problems

The traditional method of pairwise job interchange compares the cost of sequences which differ only in the interchange of two jobs. It assumes that either there are no intermediate jobs (adjacent pairwise interchange) or that the interchange can be performed no matter what the intermediate jobs are (nonadjacent pairwise interchange). We introduce a generalization that permits the pairwise interchange of jobs provided that the intermediate jobs belong to a restricted subset of jobs (subset-restricted pairwise interchange). In general, even if an adjacent interchange relation is a partial order, it need not be a precedence order. We introduce a unified theory of dominance relations based on subset-restricted interchange. This yields a precedence order for the class of unconstrained, regular, single machine scheduling problems $1\left/ r_{j}\left/ f_{\max}.\right. \right.$ Thus it applies to $1\left/ r_{j}\left/ L_{\max},\right. \right.$ $1/ r_{j},\overline{d_{j}}/ C_{\max}$, $1\left/ r_{j}\left/ \max w_{j}L_{j},\right. \right. 1\left/ r_{j}\left/ \max w_{j}C_{j},\right.\right.$ and other problems. We also show that these problems remain strongly NP-hard for interval-ordered tasks. The strength of the precedence orders was tested in a large-scale computational experiment for $1\left/ r_{j}\left/ \max w_{j}C_{j}.\right.\right.$ The results show that using the precedence orders in branch and bound algorithms speeds these up on average by about 58 percent.

Simplification techniques for EKF computations in fault diagnosis—suboptimal gains

The extended Kalman filter (EKF) is one of the most popular model-based techniques for fault detection and diagnosis. In the present study, the idea of suboptimal EKF is utilized to enhance computation efficiency without sacrificing diagnostic accuracy. In particular, a simple procedure is developed to decompose the filter model according to the precedence order of the state/parameter estimation process. As a result, a large portion of the computations needed for propagating error covariances and updating state estimates can be neglected. Extensive simulation results are also presented to demonstrate the effectiveness of these proposed techniques.

Simplification techniques for EKF computations in fault diagnosis: Model decomposition

AbstractThe extended Kalman filter (EKF) is one of the most popular model‐based techniques for fault detection and diagnosis. In this study, the suboptimal EKF technique is utilized to enhance computation efficiency without sacrificing diagnostic accuracy. In particular, three simple strategies are proposed to decompose the filter model according to the precedence order of the state/parameter estimation process. The computation load needed in fault identification can be reduced significantly by implementing all or part of these decomposed EKFs on‐line. Extensive simulation results are also presented to demonstrate the effectiveness of these proposed techniques.

Methods for task allocation via agent coalition formation

Task execution in multi-agent environments may require cooperation among agents. Given a set of agents and a set of tasks which they have to satisfy, we consider situations where each task should be attached to a group of agents that will perform the task. Task allocation to groups of agents is necessary when tasks cannot be performed by a single agent. However it may also be beneficial when groups perform more efficiently with respect to the single agents' performance. In this paper we present several solutions to the problem of task allocation among autonomous agents, and suggest that the agents form coalitions in order to perform tasks or improve the efficiency of their performance. We present efficient distributed algorithms with low ratio bounds and with low computational complexities. These properties are proven theoretically and supported by simulations and an implementation in an agent system. Our methods are based on both the algorithmic aspects of combinatorics and approximation algorithms for NP-hard problems. We first present an approach to agent coalition formation where each agent must be a member of only one coalition. Next, we present the domain of overlapping coalitions. We proceed with a discussion of the domain where tasks may have a precedence order. Finally, we discuss the case of implementation in an open, dynamic agent system. For each case we provide an algorithm that will lead agents to the formation of coalitions, where each coalition is assigned a task. Our algorithms are any-time algorithms, they are simple, efficient and easy to implement.

Fast algorithms for compressed multimethod dispatch table generation

The efficiency of dynamic dispatch is a major impediment to the adoption of multimethods in object-oriented languages. In this article, we propose a simple multimethod dispatch scheme based on compressed dispatch tables. This scheme is applicable to any object-oriented language using a method precedence order that satisfies a specific monotonous property (e.g., as Cecil and Dylan) and guarantees that dynamic dispatch is performed in constant time, the latter being a major requirement for some languages and applications. We provide efficient algorithms to build the dispatch tables, provide their worst-case complexity, and demonstrate the effectiveness of our scheme by real measurements performed on two large object-oriented applications. Finally, we provide a detailed comparison of our technique with other existing techniques.

TWO-MACHINES SCHEDULING PROBLEM WITH FUZZY ALLOWABLE TIME CONSTRAINT

We have already introduced many fuzzy concepts to scheduling problem and discussed so called fuzzy scheduling problems. In this paper, we introduce fuzzy allowable time concept newly to two identical machine problem, which is a fuzzy version of M. R. Garey and D. S. Johnson. That is, there are two identical machines and fuzzy ready times and deadlines are associated to each job, i.e., membership function representing a satisfaction degree of start times and completion times are considered to each job and minimal one of them is to be maximized. Further among jobs, there exists fuzzy precedence relation, which is a fuzzy relation with membership function representing satisfaction degree of precedence order of each job pair and again minimal one of them is to be maximized. The aim is to maximize both minimal degrees at a time if possible, but usually there exists no schedule maximizing both of them, and so we seek nondominated schedules.

A monotonic superclass linearization for Dylan

Object-oriented languages with multiple inheritance and automatic conflict resolution typically use a linearization of superclasses to determine which version of a property to inherit when several superclasses provide definitions. Recent work has defined several desirable characteristics for linearizations, the most important being monotonicity, which prohibits inherited properties from skipping over direct superclasses. Combined with Dylan's sealing mechanism, a monotonic linearization enables some compile-time method selection that would otherwise be impossible in the absence of a closed-world assumption.The Dylan linearization is monotonic, easily described, strictly observes local precedence order, and produces the same ordering as CLOS when that is monotonic. We present an implementation based on merging and a survey of class heterarchies from several large programs, analyzing where commonly used linearizations differ.

Managing integrity in design information flows

This paper addressses integrity rules that are embedded within engineering design applications and that apply between applications. A representation for integrity rules that are embedded in applications is presented and a set of related methods developed for: (a) maintaining the integrity condition of application developed data, (b) managing the precedence order between applications, in the context of (c) changing the schema and the associated mix of applications and (d) iterated execution of applications and change propagation. Both integrity rules literally embedded within external applications and others required to be embedded within a database are considered. The techniques are demonstrated with an extensive example.

KIRCHHOFF'S LAW AND LOOP-BREAKING FOR THE DESIGN OF HEAT EXCHANGER NETWORKS

Traditional evolutionary methods for the synthesis of heat exchanger networks normally produce an initial network containing excess units when compared to the minimum units target. Subsequently, this network is simplified by energy relaxation. However, current methods fail to guarantee that the evolution follows a pathway ensuring that the minimum energy penalty is incurred. A new method to guide this evolution is presented. It is based on the application of Kirchhoff's Law to the network. This enables easy prediction of the actual energy penalties incurred by instituting different loop-breaking strategies. The minimum energy penalty may be discovered and the units to be removed to constitute an optimal solution readily identified. The precedence order for loop breaking in networks containing multiple loops can also be determined according to their respective energy penalties. The proposed algorithm enables the designer to undertake the loop-breaking phase of network design with confidence. The minimum energy path may be followed until a final network is discovered.

Nonequilibrium response in attenuating smooth plane-wave fronts

It has been clarified in an earlier work [Y. Sano, J. Appl. Phys. 65, 3857 (1989)] that the locations of attenuating peaks in smooth strain, particle velocity, and stress profiles in a smooth plane-wave front differ, that is, the order of peak precedence is stress, particle velocity, and strain. As a result of the precedence order, the wave front composed of elementary waves such as a contraction wave C, mesocontraction waves I and II, and a vice-rarefaction wave R was formed. That the process is degraded by another rarefaction wave Rb which first follows the wave R, and then outruns the waves R, II, and I in sequence, has also been proved. [Y. Sano, J. Appl. Phys. 67, 4072 (1990)]. After the completion of the degradation process, the wave front, i.e., the wave C, may attenuate little, but steepen. This paper extends the process under consideration to include the steepening process during which the wave C approaches a steady state. In addition to this extension, stationary phenomena in strain, particle velocity, and stress-time profiles are shown to be able to take place in the degradation process. It is one of the main purposes of this paper to show through the phenomena that the response caused by the wave fronts during the process will be unsteady and nonequilibrium. Furthermore, universal properties of the stress-particle velocity paths are clarified. The properties involve concavity or convexity of the path curves produced by the waves C, I, II, and R. Universal properties of the stress-strain paths such as concavity, convexity, or inflection of the path curves by the waves C, I, II, and R are also clarified. Through the behavior of the stress-particle velocity and stress-strain paths having the properties mentioned above, it is also shown that the response caused by the waves will be unsteady and nonequilibrium. The stationary phenomena, the universal properties, and the stress-particle velocity and stress-strain behaviors are compared with the previous experiments and computational data. Another main purpose of this paper is to confirm through comparison the occurrence of the elementary waves and the degradation process in the experiments.