Abstract
Make-to-order companies, such as job shops, have been extensively studied. Some of those studies emphasise the importance of the workload control in order to improve manufacturing operations. In this paper a multiple decision-making scheme, with the purpose of planning and controlling operations and getting better delivery and workload related performance measures, as well as one order release decision rule are proposed. The decision-making scheme includes four main decisions: (i) accept or reject an in-coming order; (ii) define the order's due date; (iii) release the accepted jobs; and (iv) dispatch the jobs at the station level. Extensive simulation experiments were performed to compare the proposed rule with the benchmark mechanisms, as well as with rules presented in previous studies. They led to the conclusion that considering the four decisions simultaneously can improve the job shop measures of performance, and that the proposed release rule is the best in almost all instances.

Abstract
Controlling the flow of materials inside job-shops involves several decisions such as the acceptance or rejection of an incoming order, the order's due date definition, the releasing and the dispatching of the job. This study applies a multiple decision-making scheme involving these four decision phases to examine the sensitivity of job-shop performance to different order release parameters. The performance criteria of shop workload and order delivery were collected to demonstrate the influence of the most significant order release parameters: the queue workload limit and the planning parameter of the latest release date. The influence of each parameter is evaluated by computational simulations. The way we compute the machine workload limit affects not only the workload but also delivery performance measures. However, surprisingly, the latest release date has not a significant impact on shop-floor performance measures. The effect of the queue workload limit in an input-output control. mechanism on delivery and workload related performance measures had not been studied up to date. Neither any analysis had investigated the influence of the latest release date calculus on the performance of the job-shop.

Abstract
In this paper we present three hybrid heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. Our heuristic is a combination of a steady-state genetic algorithm and three improvement procedures. The two computationally less expensive of these three improvement procedures are used inside the genetic algorithm to improve the schedule obtained after the application of genetic operators, whereas the more expensive one is used to improve the best solution returned by the genetic algorithm. We have compared our hybrid approaches against existing recovering beam search and genetic algorithms. The computational results show the effectiveness of our hybrid approaches. Indeed, our hybrid approaches outperformed the existing heuristics in terms of solution quality as well as running time.

Abstract
In this paper, we consider the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. We propose a genetic approach based on a random key alphabet and present several algorithms based on this approach. These versions differ on the generation of both the initial population and the individuals added in the migration step, as well as on the use of local search. The proposed procedures are compared with the best existing heuristics, as well as with optimal solutions for the smaller instance sizes. The computational results show that the proposed algorithms clearly outperform the existing procedures and are quite close to the optimum. The improvement over the existing heuristics increases with both the difficulty and the size of the instances. The performance of the proposed genetic approach is improved by the initialization of the initial population, the generation of greedy randomized solutions, and the addition of the local search procedure. Indeed, the more sophisticated versions can obtain similar or better solutions and are much faster. The genetic version that incorporates all the considered features is the new heuristic of choice for small and medium size instances.

Abstract
In this paper, we present greedy randomised dispatching heuristics for the single-machine scheduling problem with quadratic earliness and tardiness costs and no machine idle time. The several heuristic versions differ, on the one hand, on the strategies involved in the construction of the greedy randomised schedules. On the other hand, these versions also differ on whether they employ only a final improvement step or perform a local search after each greedy randomised construction. The proposed heuristics were compared with existing procedures as well as with optimum solutions for some instance sizes. The computational results show that the proposed procedures clearly outperform their underlying dispatching heuristic, and the best of these procedures provide results that are quite close to the optimum. The best of the proposed algorithms is the new recommended heuristic for large instances as well as a suitable alternative to the best existing procedure for the larger of the middle-sized instances.

Abstract
Objective - The purpose of this paper is to build a framework for an international outsourcing process in the apparel industry that can serve to support managerial decisions and actions regarding outsourcing choices and implementation. Design/methodology/approach - We developed of a straightforward and flexible framework describing the main stages of the international outsourcing process and its main activities with application in the context of the apparel industry. A case study approach was adopted with primary data collected through in-depth interviews and secondary data aggregated from company reports and documents. Theoretical foundation - Some research gaps in the outsourcing literature and most specifically on the matter of international outsourcing were identified by Hatonen and Eriksson (2009) and Kakabadse and Kakabadse (2000), among others. Specifically, these authors claim that there is not enough research on developing and offering decision models, tools or guidelines to support managerial decisions with the appropriate empirical evidence. This study aims to address this gap. Findings - We found that the international outsourcing process can be described using the proposed framework. Apparel companies can use this framework to support and supervise international outsourcing processes. Practical implications - This study provides a simple model that can help companies in the apparel industry to enhance their outsourcing activities and operations, and also contributes to a broader academic understanding of the matter.