Abstract
In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers.

Abstract
Numerical study is provided of the methods for solving the facility location problem when the clients choose some suppliers by their own preferences. Various formulations of this problem as an integer linear programming problem are considered. The authors implement a cutting plane method based on the earlier proposed family of valid inequalities which arises from connection with the problem for a pair of matrices. The results of numerical experiment are presented for testing this method. An optimal solution is obtained by the two versions of the branch and cut method with the suggested cutting plane method. The simulated annealing method is proposed for obtaining the upper bounds of the optimal solution used in exact methods. Numerical experiment approves the efficiency of the implemented approach in comparison with the previously available methods. © 2010 Pleiades Publishing, Ltd.

Abstract
In this paper, an integer programming model for two-dimensional cutting stock problems is proposed. In the problems addressed, it is intended to cut a set of small rectangular items of given sizes from a set of larger rectangular plates in such a way that the total number of used plates is minimized. The two-stage and three-stage, exact and non-exact, problems are considered. Other issues are also addressed, as the rotation of items, the length of the cuts and the value of the remaining plates. The new integer programming model can be seen as an extension of the "one-cut model" proposed by Dyckhoff for the one-dimensional cutting stock problem. In the proposed model, each decision variable is associated with cutting one item from a plate or from a part of a plate resulting from previous cuts (residual plates). Comparative computational results of the proposed model and of models from the literature are presented and discussed.

Abstract
Customer satisfaction (CS) and retention are key issues for organisations in today's competitive market place, making its proper evaluation a main concern for companies. Recently, the European Customer Satisfaction Index (ECSI) has been assumed as a reliable and independent frame-of-reference way of assessing CS. This article describes one framework based on ECSI, which attempts to evaluate the factors that contribute to CS for the Portuguese moulds industry. In order to pursue this goal, an ECSI model, specific for the injection mould industry, was designed and tested. Owing to the characteristics of the gathered data, partial least squares was used to estimate model parameters. The estimated model, which shows validity and reliability, demonstrates an excellent capacity for explaining CS (80.4%), as well as loyalty (58.2%). We also propose an approach to link the ECSI model parameters to the generation and evaluation of design solutions for moulds. This linkage allows us to identify the critical factors for achieving high levels of molds' design quality, through analytical hierarchical process (AHP) ranking, and to determine the impact of mould's design solutions over CS and retention.

Abstract
The aim of this paper is to contribute to a better understanding of the determinants of public service quality. Firstly, it explores the relationships that develop during the public service encounter between the citizen, the public organization and society. Secondly, citizen satisfaction and dissatisfaction with public services are both investigated. Furthermore, the paper emphasizes the importance of managing emotions in public services. Finally, it also considers how the quality assessment of public services should take into account implications regarding value to society. The outcome is a holistic model for assessing the quality of public services. © 2010 Springer-Verlag.

Abstract
The design of injection molding systems for plastic parts relies heavily on experience and intuition. Recently, mold makers have been compelled to shorten lead times, reduce costs and improve process performance due to global competition. This paper presents a framework, based on a Multidisciplinary Design Optimization (MDO) methodology, which tackles the design of an injection mold by integrating the structural, feeding, ejection and heat-exchange sub-systems to achieve significant improvements. To validate it single objective optimization is presented leading to a 42% reduction in cycle time. We also perform multiple objective optimization simultaneously minimizing cycle time, wasted material and pressure drop. Sensitivity analysis shows a large impact of the sprue diameter (> 1.5 normalized sensitivity) highlighting the importance of the feeding subsystem on overall quality. The results show substantial improvements resulting in reduced rework and time savings for the entire mold design process.