Catálogo de publicaciones - libros

In this paper, we propose a queueing model for a multi-product production system in which the manufacturing environments are changing over time between some predetermined states. We model this system by the discrete-time Markovian Arrival Stream (MAS) and derive the mean level of WIP (work-in-process) inventory. A numerical example is presented.

In this study, we propose an improved version of the dynamic movement-based location update scheme that stores all cells visited by the MS, and their neighboring cells, to reduce the location update cost of the dynamic movement-based location update scheme. We show that a significant reduction in the location update cost is achieved in our scheme. We also show that our scheme has optimal total cost when the threshold is rather small. Additionally, the MS requires a minimal amount of memory to successfully implement our scheme.

In this paper we present a nonlinear programming solution to one of the most challenging problems in trajectory optimization. Unlike most aerospace trajectory optimization problems the ascent phase of a hypersonic vehicle has to undergo large changes in altitude and associated aerodynamic conditions. As a result, its aerodynamic characteristics, as well as its propulsion parameters, undergo drastic changes. Further, the data available through wind tunnel tests are not always smooth. The challenge in solving such problems lies both in the preprocessing of the data as well as in the judicious use of optimization techniques. In this paper we advocate approximation of the infinite dimensional optimal control problem, derived from practical considerations of a hypersonic vehicle ascending from an altitude of 16 kms to an altitude of 32 kms with specified mach numbers, into a set of finite dimensional nonlinear programming problems. This finite dimensional approximation is shown to produce acceptable optimized results in terms of angle-of-attack control histories and state behaviour. A modification, that exploits the ultimate scheme of linear interpolation of the optimal discrete history, is proposed and is shown to produce accurate results with smaller number of grid points.

In this paper, the imperfect maintenance model and proportional intensity model are considered for the repairable systems under accelerated stress. The age reduction model (Malik’s model) is assumed for imperfect maintenance. The stress acts multiplicatively on the baseline cumulative intensity. The log-likelihood function is derived and a maximizing procedure is proposed. In simulation studies, we investigate the accuracy and some properties of the estimation method.

As many companies are becoming environmentally conscious, and as stringent environmental laws are being passed, remanufacturing has received growing attention. In this paper, we discuss the remanufacturing system where the manufacturer overhauls returned products and bringing back to ‘as new’ conditions. We propose two mathematical models for consecutive decision making at strategic and operational level in remanufacturing system. And sensitivity analyses are conducted on various parameters to gain insight into the proposed models by using a set of data reflecting a real business situation.

In this paper, we present a parallel tabu search (TS) algorithm for efficient optimization of a constrained multiobjective VLSI standard cell placement problem. The primary purpose is to accelerate TS algorithm to reach near optimal placement solutions for large circuits. The proposed technique employs a candidate list partitioning strategy based on distribution of mutually disjoint set of moves among the slave processes. The implementation is carried out on a dedicated cluster of workstations. Experimental results using ISCAS-85/89 benchmark circuits illustrating quality and speedup trends are presented. A comparison of the obtained results is made with the results of a parallel genetic algorithm (GA) implementation.

This paper considers the earliness and tardiness problem of sequencing a set of independent jobs on non-identical multi-machines, and explores the use of artificial neural networks as a valid alternative to the traditional scheduling approaches. A coupled gradient network approach is employed to provide a shop scheduling analysis framework. The methodology is based on a penalty function approach used to construct the appropriate energy function and a gradient type network. The mathematical formulation of the problem is firstly presented and six coupled gradient networks are constructed to model the mixed nature of the problem. After the network architecture and the energy function were specified, the dynamics are defined by steepest gradient descent algorithm.

It is well known that the traffic in computer-communication systems is autocorrelated and the correlation makes an great effect on the performances. So it is important to study the correlated arrival process to better estimate the performances at the system and Markov renewal process is considered here to model the autocorrelated arrival stream. We derive the expected number of packets at arbitrary epoch and expected delay time using supplementary variable method.

A resin manufacturer in Korea operates a large plant for synthetic resin products. The production process consists of two stages where a line in the first stage is a bottleneck of the whole process. Some low-profit products have consumed considerable amount of bottleneck capacity, and caused opportunity loss in profit generation. This is due to the traditional management policy that allows several marketing business units to plan their annual target sales individually and independently, without careful consideration of the effective use of the production capacity. Noting such marketing-production misalignment, we developed linear programming models to help determine desirable product mix while coping with market demands and production capacity.

This paper describes the optimal design and operation of an activated sludge system in wastewater treatment plants. The optimization problem is represented as a smooth programming problem with linear and nonlinear equality and inequality constraints, in which the objective is to minimize the total cost required to design and operate the activated sludge system under imposed effluent quality laws. We analyze four real world plants in the Trás-os-Montes region (Portugal) and report the numerical results obtained with the FILTER, IPOPT, SNOPT and LOQO optimizers.