In a mixed-model assembly line dierent models of a common base product can be manufactured in intermixed production sequences. A famous solution approach for the resulting short-term sequencing problem is the so called level scheduling problem, which aims at evenly smoothing the material...

In this paper we compare the performance of the Differential Evolution (DE) and the Repulsive Particle Swarm (RPS) methods of global optimization. To this end, seventy test functions have been chosen. Among these test functions, some are new while others are well known in the literature; some are...

We develop a hybrid algorithm using Genetic Algorithms (GA) and Simulated Annealing (SA) to solve multi-objective step function maximization problems. We then apply the algorithm to a specific economic problem which is taken out of the corporate governance literature.

This paper uses a multivariate regime-switching framework to investigate and endogenously date changes in return characteristics on the four largest Nordic stock markets. We find that the deregulated time-period, specifically after 1982, is associated with higher expected return, higher...

We discuss computational issues in the sequential probit model that have limited its use in applied research. We estimate parameters of the model by the method of simulated maximum likelihood (SML) and by Bayesian MCMC algorithms. We provide Monte Carlo evidence on the relative performance of...

Resource levelling techniques aim to minimize the fluctuation from one time period to another in resource usage. Except for small-sized problems, though, computational optimization procedures are inefficient when solving construction resource levelling problems. Consequently, heuristic and...

This paper presents a new approach to solve the short-term unit commitment problem using genetic algorithm-based simulated annealing method for utility system. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimised when subjected to a...