James MacGregor Smith

Multi-objective evacuation routing in transportation networks

In this paper, the optimal design and analysis of evacuation routes in transportation networks is examined. An methodology for optimal egress route assignment is suggested. An integer programming (IP) formulation for optimal route assignment is presented, which utilizes M/G/c/c state dependent queueing models to cope with congestion and time delays on road links. M/G/c/c simulation software is used to evaluate performance measures of the evacuation plan: clearance time, total travelled distance and blocking probabilities. Extensive experimental results are included.

Stochastic network evacuation models

Abstract Stochastic network evacuation models are crucial for the safe evacuation of occupants from buildings. In this paper, we compare an analytical closed queueing network and a simulation model for analyzing the evacuation of occupants from a hospital. Evacuation times, arc congestion, and optimization of the evacuation routes and staff assigned to the evacuation network are included.

Lagrangean based methods for solving large-scale cellular network design problems

The cellular network design (CND) problem is formulated as a comprehensive linear mixed integer programming model integrating the base station location (BSL) problem, the frequency channel assignment (FCA) problem and the topological network design (TND) problem. A solution algorithm based on Lagrangean relaxation is proposed for solving this complex cellular network design problem. Pursuing the optimum solution through exact algorithms to this problem appears to be unrealistic considering the large scale nature and NP-hardness of the problem. Therefore, the solution algorithm strategy consists in computing effective lower and upper bounds for the problem. Lower bounds are evaluated through a Lagrangean relaxation technique and subgradient method. A Lagrangean heuristic is developed to compute upper bounds based on the Lagrangean solution. The bounds are improved through a customized branch and bound algorithm which takes in account specific knowledge of the problem to improve its efficiency. Thirty two random test instances are solved using the proposed algorithm and the CPLEX optimization package. The results show that the duality gap is excessive, so it cannot guarantee the quality of the solution. However, the proposed algorithm provides optimal or near optimal solutions for the problem instances for which CPLEX also provides the optimal solution. It further suggests that the proposed algorithm provides optimal or near optimal solutions for the other instances too. Finally, the results demonstrate that the proposed algorithm is superior to CPLEX as a solution approach for the CND problem.

Stochastic modeling of manufacturing systems : advances in design, performance evaluation, and control issues

Factory Design.- Dilemmas in factory design: paradox and paradigm.- Unreliable Production Lines.- Lean buffering in serial production lines with non-exponential machines.- Analysis of flow lines with Cox-2-distributed processing times and limited buffer capacity.- Performance evaluation of production lines with finite buffer capacity producing two different products.- Automated flow lines with shared buffer.- Integrated quality and quantity modeling of a production line.- Stochastic cyclic flow lines with blocking: Markovian models.- Queueing Network Models of Manufacturing Systems.- Performance analysis of multi-server tandem queues with finite buffers and blocking.- An analytical method for the performance evaluation of echelon kanban control systems.- Closed loop two-echelon repairable item systems.- A heuristic to control integrated multi-product multi-machine production-inventory systems with job shop routings and stochastic arrival, set-up and processing times.- Performance analysis of parallel identical machines with a generalized shortest queue arrival mechanism.- A review and comparison of hybrid and pull-type production control strategies.- Stochastic Production Planning and Assembly.- Planning order releases for an assembly system with random operation times.- A multiperiod stochastic production planning and sourcing problem with service level constraints.

Steiner minimal trees and urban service networks

The optimal configuration of urban service networks has recently been shown to be a computationally difficult problem. However, there are efficient and effective techniques by which this optimal configuration of urban service networks can be approximated. In this paper, we analyze the Lp Steiner Network problem in the plane R2 and demonstrate its applicability to the urban service network problem. We present a simple algorithm for estimating the Lp metric parameter for random points in the plane, then utilize it to find the Lp values for four different American cities. Finally, we apply the LpSMT algorithm described within the text to one of the cities in order to demonstrate the effectiveness of our algorithm for determining optimal network configurations.

Modeling wildfire propagation with Delaunay triangulation and shortest path algorithms

In this paper, a methodology for modeling surface wildfire propagation through a complex landscape is presented. The methodology utilizes a Delaunay triangulation to represent surface fire spread within the landscape. A procedure to construct the graph and estimate the rate of spread along the edges of a network is discussed. After the Delaunay data structure is constructed, a two pass shortest path algorithm is incorporated to estimate the minimum travel time paths and fire arrival times. Experimental results are also included.

Performance analysis of open general queuing networks with blocking and feedback

Queuing network models have been extensively used for performance evaluation in many modern manufacturing and communication systems. The phenomenon of feedback reflects many practical situations, e.g. reworking in the production systems. However, existing research on open queuing network with feedback mainly concentrates on the models with infinite buffers or the models with finite buffers but exponentially distributed inter-arrival and service times. Research on open queuing networks with finite buffers, feedback and general inter-arrival and service times has not been reported. In this paper, a Rate Iterative Method embedded with the Generalised Expansion Method, is proposed for modelling this type of queuing network. System performance measures include the mean throughput, work-in-process and sojourn time all calculated by the proposed method. The accuracy and the efficiency of the proposed method are tested by comparing the results with other methods or simulation results from the experiments. Finally, a case study of a practical production system used in the manufacturing industry is studied and illustrates the applications of the proposed method. The results in this paper can be used as a basis for system design analysis and resource planning.

Editorial: Stochastic models of manufacturing and service system operations

This volume originates from the Seventh International Conference on “Stochastic Models of Manufacturing and Service Operations”, which took place in Ostuni, Italy, in 7–12 June, 2009. The aim of this conference was to serve as a forum for researchers, academics and industrialists to discuss their most recent research findings and to provide them with opportunities for technology transfer. The conference was organized by the Politecnico di Milano, the University of Salento, and ITIA-CNR, Italy. The head of the Organizing Committee was Dr. Tullio Tolio, Professor at the Politecnico di Milano and Director of ITIA-CNR. The conference attracted thirty-three international scholars who presented their work in single-track sessions and many more that participated. Professor Horst Tempelmeier of the University of Cologne, Germany, gave the plenary talk. The previous six biannual conferences of this series were held in Greece (1997–2005) and the Netherlands (2007) under the name “International Conference on Analysis of Manufacturing Systems” and variants of it. To accomplish a wider dissemination of the results that were reported at the conference, along with those obtained by other researchers working in the area of stochastic modeling

Steiner Trees and the Dynamic Quadratic Assignment Problem

Two of the most challenging problems in network design are the Quadratic Assignment Problem (QAP) and the Steiner network problem. One of the key objectives of this paper is to show the strong link between these two network design problems. Dynamic flows in QAPs are modelled as stochastic processes. The underlying flow topology is represented as a Steiner tree queueing network topology. Customers and goods flow over tandem links of the Steiner network. A heuristic for the Stochastic Quadratic Assignment Problem SQAP is developed for solving this flow network topology problem and computational experience is presented.

Simultaneous buffer and service rate allocation in open finite queueing networks

ABSTRACT Simultaneous buffer and service rate allocation in open finite queueing networks is a nonlinear mixed-integer programming problem that is -Hard. A queueing network decomposition methodology is coupled with a nonlinear sequential quadratic programming algorithm to compute the simultaneous optimal buffer allocations and service rates via a branch-and-bound scheme for various network topologies. It is shown that the optimization problem is a nonlinear convex programming problem, which assists in the search for local optimal solutions. The material handling or transportation system for transferring the finite customer population between the nodes in the network is also included. Extensive numerical results demonstrate the efficacy of the methodology for series, split, and merge topology networks. Examination of the persistence or absence of the allocation patterns of the service rates and buffers is one of the focal points of this work.