Local decision making and decision fusion in hierarchical levels

Hierarchical problem solving is preferred when the problem is overwhelmingly complicated. In such a case, the problem should better be analyzed in hierarchical levels. At each level, some temporary solutions are obtained; then a suitable decision fusion technique is used to merge the temporary solutions for the next level. The hierarchical framework proposed in this study depends on reutilization or elimination of previous level local agents that together perform the decisions due to a decision-fusion technique: a performance criterion is set for local agents. The criterion checks the success of agents in their local regions. An agent satisfying this criterion is reutilized in the next level, whereas an agent not successful enough is removed from the agent pool in the next level. In place of a removed agent, a number of new local agents are developed. This framework is applied on a fault detection problem.      

A dynamic stochastic version of the pitcher‐hamblin‐miller model of “collective violence*

The central equation of the deterministic diffusion model of Pitcher, Hamblin, and Miller (1978) is formulated as a time‐inhomogeneous stochastic process. It will be shown that the stochastic process leads to a negative binomial distribution. The deterministic diffusion function can be derived from the stochastic model and is identical to the expected value as a function of time. Therefore the deterministic model is supported in terms of the underlying stochastic process. Moreover the stochastic model allows the prediction of the distribution for any point in time and the construction of prediction intervals.     

Distributed decision making––a unified approach

The paper gives an overview over the broad area of distributed decision making (DDM). In achieving a systematic procedure a general framework is developed that allows to describe the numerous approaches in DDM in a unified way. Focusing on application areas the paper is not only considering various fields in the management sciences, like hierarchical production planning, supply chain management, or managerial accounting, but is regarding other disciplines as well. Particularly, economics and computer sciences are investigated as to their specific contributions to DDM. It turns out that each field and discipline elaborate different aspects of DDM which particularly for OR could be used to solve concrete highly involved DDM problems.     

Heavy traffic resource pooling in parallel‐server systems

We consider a queueing system with r non‐identical servers working in parallel, exogenous arrivals into m different job classes, and linear holding costs for each class. Each arrival requires a single service, which may be provided by any of several different servers in our general formulation; the service time distribution depends on both the job class being processed and the server selected. The system manager seeks to minimize holding costs by dynamically scheduling waiting jobs onto available servers. A linear program involving only first‐moment data (average arrival rates and mean service times) is used to define heavy traffic for a system of this form, and also to articulate a condition of overlapping server capabilities which leads to resource pooling in the heavy traffic limit. Assuming that the latter condition holds, we rescale time and state space in standard fashion, then identify a Brownian control problem that is the formal heavy traffic limit of our rescaled scheduling problem. Because of the assumed overlap in server capabilities, the limiting Brownian control problem is effectively one‐dimensional, and it admits a pathwise optimal solution. That is, in the limiting Brownian control problem the multiple servers of our original model merge to form a single pool of service capacity, and there exists a dynamic control policy which minimizes cumulative cost incurred up to any time t with probability one. Interpreted in our original problem context, the Brownian solution suggests the following: virtually all backlogged work should be held in one particular job class, and all servers can and should be productively employed except when the total backlog is small. It is conjectured that such ideal system behavior can be approached using a family of relatively simple scheduling policies related to the cμ rule. This revised version was published online in June 2006 with corrections to the Cover Date.     

Attractors for partly dissipative lattice dynamic systems in l2×l2

In this paper, we study the asymptotic behavior of solutions for the partly dissipative lattice dynamical systems in $l^2\times l^2$. We prove the asymptotic compactness of the solutions and then establish the existence of the global attractor in $l^2\times l^2$. The upper semicontinuity of the global attractor is also considered by finite-dimensional approximations of attractors for the lattice systems.     

Static and dynamic server allocation in systems with on/off sources

A system consisting of a number of servers, where demands of different types arrive in bursts (modelled by interrupted Poisson processes), is examined in the steady state. The problem is to decide how many servers to allocate to each job type, so as to minimize a cost function expressed in terms of average queue sizes. First, an exact analysis is provided for an isolated IPP/M/n queue. The results are used to compute the optimal static server allocation policy. The latter is then compared to four heuristic policies which employ dynamic switching of servers from one queue to another (such switches take time and hence incur costs). This work was carried out in the framework of the collaborative project DOPCHE (Dynamic Operative Policies for Commercial Hosting Environments), funded by the UK Engineering and Physical Sciences Research Council under its E-Science programme. The support of the Network of Excellence EuroNGI, funded by the EU, is also acknowledged.     

Asymptotic behaviour of dynamic systems on time scales†

This paper is concerned with asymptotic behaviour of solutions of perturbed dynamic systems on time scales. A time scale version of the Hartman–Wintner theorem is established for a class of time scales.     

Multi-component Cahn–Hilliard systems with dynamic boundary conditions

Our aim in this paper is to study the well-posedness and the asymptotic behavior, in terms of finite-dimensional attractors, of Cahn–Hilliard systems describing phase separation processes in multi-component alloys, endowed with dynamic boundary conditions. Such boundary conditions take into account the interactions with the walls when considering confined systems.     

A unified framework for pull control mechanisms in multi‐stage manufacturing systems

This paper presents a unified framework for pull production control mechanisms in multistage manufacturing systems. A pull production control mechanism in a multistage manufacturing system is a mechanism that coordinates the release of parts into each stage of the system with the arrival of customer demands for final products. Four basic pull production control mechanisms are presented: Base Stock, Kanban, Generalized Kanban, and Extended Kanban. It is argued that on top of any of these basic coordination mechanisms, a local mechanism to control the workinprocess in each stage may be superimposed. Several cases of basic stage coordination mechanisms with stage workinprocess control are presented, and several production control systems that have appeared in the literature are shown to be equivalent to some of these cases.     

Income redistribution policies and decision support systems — Problems and potentials

Recent trends in Western industrial countries towards a re-examination of the means and goals of the welfare state have increased the demand for studies of the redistributive effects of government policies. The purpose of this paper is to discuss some problems and potentials of decision support systems in this field, with emphasis on the problems of value judgements and evaluation criteria and with reference to the author's experiences from the development of an interactive computer model of the Swedish tax and transfer system. The basic structure of the model and some examples of its application are briefly described.     

Soft set theory and uni–int decision making

We firstly redefine the operations of Molodtsov’s soft sets to make them more functional for improving several new results. We also define products of soft sets and uni–int decision function. By using these new definitions we then construct an uni–int decision making method which selects a set of optimum elements from the alternatives. We finally present an example which shows that the method can be successfully applied to many problems that contain uncertainties.     

Semi‐Markov compartmental systems with branching particles

A semi‐Markov compartmental system in which the particles reproduce according to the Markov branching process, apart from transitions between the compartments, is considered. Asymptotic behaviour of the mean matrix of the number of particles alive at time t is studied. Explicit expressions for some special cases are discussed.     

Sociometric triads as multi‐variate systems†

Binary choices (choose v. not choose) among three persons may be viewed as variables and the possible choices in a triad as a 64 celled contingency table, amenable to analysis in terms of log linear effects. Fifteen non‐redundant effects occur, of which four appear consistently in a data bank of 384 sociograms. Consequently, it is claimed one may reproduce the triad frequencies in most sociograms by the effects implied by four propositions: (A) P is more likely to choose O when O chooses P, net of all other variables; (B) P is more likely to choose O when X chooses O. This association is particularly strong when imitation produces transitivity; (C) when X chooses O (O chooses X), P tends to choose both or neither; and (D) P tends to choose an X who favors P's choices. P tends to not choose an X who favors P's non‐choices.     

Equilibrium models for inter‐dependent Markov systems

A Markovian model of graded systems, like the educational system, ensures internal consistency between forecasts. Sometimes merely ensuring this consistency is not enough, for the stochastic system may be operating below desired planning levels. This is highlighted. The educational system is considered and necessary conditions for equilibrium between demand and supply of teachers at first level is given. Disequilibrium conditions are shown to exist when the resulting models are applied to an autonomous education zone.     

Using aggregate fill rate for dynamic scheduling of multi-class systems

For dynamic scheduling of multi-class systems where backorder cost is incurred per unit backordered regardless of the time needed to satisfy backordered demand, the following models are considered: the cost model to minimize the sum of expected average inventory holding and backorder costs and the service model to minimize expected average inventory holding cost under an aggregate fill rate constraint. Use of aggregate fill rate constraint in the service model instead of an individual fill rate constraint for each class is justified by deriving equivalence relations between the considered cost and service models. Based on the numerical investigation that the optimal policy for the cost model is a base-stock policy with switching curves and fixed base-stock levels, an alternative service model is considered over the class of base-stock controlled dynamic scheduling policies to minimize the total inventory (base-stock) investment under an aggregate fill rate constraint. The policy that solves this alternative model is proposed as an approximation of the optimal policy of the original cost and the equivalent service models. Very accurate heuristics are devised to approximate the proposed policy for given base-stock levels. Comparison with base-stock controlled First Come First Served (FCFS) and Longest Queue (LQ) policies and an extension of LQ policy (Δ policy) shows that the proposed policy performs much better to solve the service models under consideration, especially when the traffic intensity is high.