A multi-objective scatter search for a mixed-model assembly line sequencing problem

A mixed-model assembly line (MMAL) is a type of production line where a variety of product models similar to product characteristics are assembled. There is a set of criteria on which to judge sequences of product models in terms of the effective utilization of this line. In this paper, we consider three objectives, simultaneously: minimizing total utility work, total production rate variation, and total setup cost. A multi-objective sequencing problem and its mathematical formulation are described. Since this type of problem is NP-hard, a new multi-objective scatter search (MOSS) is designed for searching locally Pareto-optimal frontier for the problem. To validate the performance of the proposed algorithm, in terms of solution quality and diversity level, various test problems are made and the reliability of the proposed algorithm, based on some comparison metrics, is compared with three prominent multi-objective genetic algorithms, i.e. PS-NC GA, NSGA-II, and SPEA-II. The computational results show that the proposed MOSS outperforms the existing genetic algorithms, especially for the large-sized problems.     

On Suitability of the Averaged Strain Energy Density Criterion in Predicting Mixed Mode I/Ii Brittle Fracture of Blunt V-Notches with Negative Mode I Contributions

Strength of Materials - The main goal of the present research is to check the suitability of the well-known brittle fracture criterion, namely the averaged strain energy density (ASED), in...     

Performance analysis of multiuser selection diversity in SIMO spectrum sharing systems

In this paper, a performance analysis is presented for user selection schemes in a single‐input multiple‐output spectrum sharing system. In the considered system, multiple secondary users try to use the licensed spectrum of a primary user in an opportunistic manner, in which an interference constraint for the primary user is satisfied. In this paper, we first use 2 conventional user selection schemes for single‐input multiple‐output spectrum sharing system and analyze the system performance for each scheme. We then propose a new user selection scheme that can overcome the limitations of those 2 conventional user selection schemes. As for the performance analysis, the average channel capacity, the outage probability, and the bit error rate performances of the system using the presented user selection schemes are analyzed and mathematical closed‐form expressions for the outage probability are derived. The performances of the system are evaluated using the derived mathematical formulas in different cases. In addition, Monte Carlo simulation results are also provided to show the accuracy and correctness of the performed analysis.     

Not Waving,Drowning: Can Local Government Policies on Climate Change Adaptation and Disaster Resilience Make a Difference?

Climate change will increase the intensity, duration and/or frequency of some climate-related hazards. Responsibility for adapting to such impacts of climate change in Australia has, in the main, fallen on local governments which have paid varying degrees of attention to the issue. This paper takes an integrated approach to compare the climate adaptation and disaster resilience policies and plans of local governments of two low-lying coastal cities in Australia to understand whether (and how) local governments can make a difference. The findings indicate that local governments can significantly contribute to building resilience and adapting to climate-related hazards, however a number of factors such as the attitudes of local governments on climate change, environmental activism, and the recent experiences of climate-related disasters are instrumental for shaping a better local response. Local action also needs to be supported by a more integrated approach by all levels of government.     

A new analytical model to predict heavy oil production rate in the SAGD process

An analytical model for predicting the oil production rate in the steam-assisted gravity drainage (SAGD) process is presented in this article. The suggested correlation is found based on Butler's original work. It considers the most effective parameters of the process that emphasize the influence of gravity drainage and that are grouped together in the form of the Rayleigh's number. The present model introduces three coefficients (i, j, and k) into the equation, which are determined by minimizing an objective function based on the difference between the six experimental SAGD datasets and the calculated results. The tool chosen for the minimization is the genetic algorithm (GA). After the initial evaluation, the same approach is used for other reservoir characteristics to ensure the robustness of the new equation. Having considered various simulation outcomes with an average error of 8.9% makes this model a credible one for predicting the SAGD production rates. The novelty of the new predictive model lies within its unique approach, making it quite fast and applicable to a wide range of reservoirs with low associated estimation inaccuracies.