On q-orthogonal polynomials over a collection of complex origin intervals related to little q-Jacobi polynomials

We construct the sequence of orthogonal polynomials with respect to an inner product which is defined by q-integrals over a collection of intervals in the complex plane. We prove that they are connected with little q-Jacobi polynomials. For such polynomials we discuss a few representations, a recurrence relation, a difference equation, a Rodrigues-type formula and a generating function. 2000 Mathematics Subject Classification Primary—33D45, 42C05     

On the Intersection Problem for Steiner Triple Systems of Different Orders

A Steiner triple system of order v, or STS(v), is a pair (V, ) with V a set of v points and a set of 3-subsets of V called blocks or triples, such that every pair of distinct elements of V occurs in exactly one triple. The intersection problem for STS is to determine the possible numbers of blocks common to two Steiner triple systems STS(u), (U, ), and STS(v), (V, ), with U⊆V. The case where U=V was solved by Lindner and Rosa in 1975. Here, we let U⊂V and completely solve this question for v−u=2,4 and for v≥2u−3. supported by NSERC research grant #OGP0170220. supported by NSERC postdoctoral fellowship. supported by NSERC research grant #OGP007621.     

Embeddings of resolvable group divisible designs with block size 3

It is proved in this paper that an RGD(3, g;v) can be embedded in an RGD(3, g;u) if and only if , , , v ≥ 3g, u ≥ 3v, and (g,v) ≠ (2,6),(2,12),(6,18).     

When does management matter in a dog-eat-dog world: An “Interaction Value Analysis” model of organizational climate

Interaction Value Interaction Value Analysis (I.V.A.) models a network of rational actors who generate value by interacting with each other. This model can be used to understand human organizations. Since people form organizations to facilitate interactions between productive individuals, the value added by interaction is the contribution of the organization. This paper examines the result of varying the queuing discipline used in selecting among back-logged interaction requests. Previously developed I.V.A. models assumed a First-in-first-out (FIFO) discipline, but using other disciplines can better represent the “Climate” of an organization. I.V.A. identifies circumstances under which organizations that control members’ interaction choices outperform organizations where individuals choose their own interaction partners. Management can be said to “matter” when individual choices converge to a point where interactions generate a lower than optimal value. In previous I.V.A. models, relinquishing central control of interaction choices reduced the aggregate value by anything from 0% to 12%, depending on circumstances. This paper finds the difference between the two modes of organization to go as high as 47% if actors display preferences between interaction partners instead of treating all equally. A politically divided, dog-eat-dog, “Capitalist” climate follows one queuing discipline, which is found to generally increase the value that a strong control structure can add. A chummy, in-bred “Fraternal” climate gains from control in some circumstances (low interdependence or low differentiation), but not in others (high or medium interdependence and differentiation under low diversity, for example). These are compared to the previous version of I.V.A., in which the queuing discipline was FIFO and the climate deemed “Disciplined”. Previously published findings on Organizational Climate are duplicated and extended with a higher level of detail. Priority queuing in an I.V.A. model is thus a useful proxy for Organizational Climate, open to future validation because its detailed predictions can be confirmed or falsified by observation. Walid Nasrallah is currently Assistant Professor in the Engineering Management program at the American University of Beirut (AUB). He received his Ph.D. from the Construction Engineering and Management program at Stanford University in 2000 and his Master’s degree at MIT in 1989. Between the two, he occupied several positions in the construction and software engineering fields. His research interests today include simulation, decision theory, and the evolution of organizations in response to new technologies.     

A new mixed integer programming formulation for facility layout design using flexible bays

This paper presents a mixed-integer programming formulation to find optimal solutions for the block layout problem with unequal departmental areas arranged in flexible bays. The nonlinear department area constraints are modeled in a continuous plane without using any surrogate constraints. The formulation is extensively tested on problems from the literature.     

A profit-maximizing supply chain network design model with demand choice flexibility

We present a profit-maximizing supply chain design model in which a company has flexibility in determining which customers to serve. The company may lose a customer to competition if the price it charges is too high. We show the problem formulation and solution algorithm, and discuss computational results.     

Commuting and stable feedback design for switched linear systems

In the paper, commuting and stable feedback design for switched linear systems is investigated. This problem is formulated as to build up suitable state feedback controller for each subsystem such that the closed-loop systems are not only asymptotically stable but also commuting each other. A new concept, common admissible eigenvector set (CAES), is introduced to establish necessary/sufficient conditions for commuting and stable feedback controllers. For second-order systems, a necessary and sufficient condition is established. Moreover, a parametrization of the CAES is also obtained. The motivation comes from stabilization of switched linear systems which consist of a family of LTI systems and a switching law specifying the switching between them, where if all the subsystems are stable and commuting each other, then the total system is stable under arbitrary switching.     

An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem

In this paper we propose an Ant Colony Optimisation (ACO) algorithm for defining the signal settings on urban networks following a local approach. This consists in optimising the signal settings of each intersection of an urban network as a function only of traffic flows at the accesses to the same intersection, taking account of the effects of signal settings on costs and on user route choices. This problem, also known as Local Optimisation of Signal Settings (LOSS), has been widely studied in the literature and can be formulated as an asymmetric assignment problem. The proposed ACO algorithm is based on two kinds of behaviour of artificial ants which allow the LOSS problem to be solved: traditional behaviour based on the response to pheromones for simulating user route choice, and innovative behaviour based on the pressure of an ant stream for solving the signal setting definition problem. Our results on real-scale networks show that the proposed approach allows the solution to be obtained in less time but with the same accuracy as in traditional MSA (Method of Successive Averages) approaches.     

Network design problem with relays: A genetic algorithm with a path-based crossover and a set covering formulation

The network design problem with relays arises in telecommunications and distribution systems where the payload must be reprocessed at intermediate stations called relays on the route from its origin to its destination. In fiber-optic networks, for example, optical signals may be regenerated several times to overcome signal degradation because of attenuation and other factors. Given a network and a set of commodities, the network design problem with relays involves selecting network edges, determining a route for each commodity, and locating relays to minimize the network design cost. This paper presents a new formulation to the problem based on set covering constraints. The new formulation is used to design a genetic algorithm with a specialized crossover/mutation operator which generates a feasible path for each commodity, and the locations of relays on these paths are determined by solving the corresponding set covering problem. Computational experiments show that the proposed approach can outperform other approaches, particularly on large size problems.     

带平衡约束的离散网络平衡设计问题的遗传算法

本文研究了带平衡约束的离散网络设计问题及其求解算法.模型中上层是一个离散网络设计的数学规划模型,采用遗传算法来求解.下层是采用变分不等式描述的用户平衡配流问题,利用对角化方法直接求解.通过实例对算法进行验证,结果表明该算法是有效的.