Abstract
The retail industry is becoming increasingly competitive; as a result, companies are seeking to reduce inefficiencies in their supply chains. One way of increasing the efficiency of operations inside a warehouse is by better allocating products in the available spaces. In this paper, we propose a new heuristic approach to solving the storage location assignment problem (SLAP) considering precedence constraints, in multi-aisle, multi-product picking warehouses. A two-phase heuristic procedure is developed: the products are clustered and assigned to the available spaces. We tested the procedure in the non-perishables warehouse of a real-world Portuguese retail chain, which supplies 191 stores per day. The results show that the new assignment of products allows for an improvement of up to 15% on the distance travelled by the pickers, which implies savings of approximately 477 km per month. This problem is a special case of SLAP since we are dealing with large percentages of non-uniform products. This procedure incorporates four relevant criteria for the allocation decision: the products' similarity, demand and weight, and the distance travelled by the picker. By using a two-phase heuristic method, this study offers companies and academics an alternative and more effective solution for SLAP than the usual methods based on the creation of density zones.

Abstract
This research aims to highlight the major domains of and address the most prominent topics in the Total Quality Management (TQM) field in the service sector. Although there are numerous studies related to TQM, systematic quantitative reviews on TQM in services are scarce. The objective of this paper is to present a thorough analysis of the current mostly discussed issues related to the use of TQM in services by conducting a bibliometric analysis of the extant literature on TQM collected from Web of Science and Scopus databases. The findings indicate that TQM implementation is not a fading topic. The studies in the field of 'TQM use in services' are growing and becoming more intensive. TQM-related practices are gaining more attention while the TQM implementation framework is still under development. Healthcare is the most researched industry. Top management commitment/leadership is a critical construct and managers should be aware of the obstacle caused by lacking it. TQM professionals and managers in the service sector can benefit from this paper by having a sketch of the latest and most prominent academic findings and thus gaining insights on techniques that fit into TQM implementation. For academic professionals, several research avenues are pointed out.

Abstract
This paper presents and evaluates an order release decision rule in a job-shop, based on the input-output control concept. The order release mechanism is part of a global decision-making scheme that includes four main decisions: accept/reject orders, define the order's due date, release the accepted jobs and dispatch it on the shop floor. This paper also presents an evaluation of two acceptance rules, four release mechanisms, and two dispatching rules, using four levels of due date tightness. Extensive simulation experiments were performed to compare the different decision rules, using several criteria: mean tardiness, percent tardy, mean absolute deviation, mean queue time in the shop floor and in the system, and machine usage. We conclude that considering the four decisions simultaneously improve the job-shop performance, and planning both the input and the output when deciding to release a job, leads to an improvement of the operational performance measures. Copyright © 2012 Inderscience Enterprises Ltd.

Abstract
There has been extensive research on workload and input-output control with the objective of improving manufacturing operations in job-shops. In this paper, a multiple decision-making scheme is proposed to plan and control operations in a general job-shop, and to improve delivery and workload related performance measures. The job-shop characteristics reinforce the need for designing a global system that controls both the jobs entering (order acceptance, due date setting and job release) and the work-in-process (dispatching), leading to an improvement of operational measures. Previous research has concentrated on scheduling a set of orders through the shop floor, according to some decision mechanism, in order to optimise some measure of performance (usually total lead time). This means that, since only a part of the decision-making system is being optimised, the resulting decision may be sub-optimal. In this paper it is shown that the performance of the different decision rules changes when they are considered simultaneously. Hence, a higher level approach, where the four decisions (order acceptance, due date setting, job release and dispatching) are considered at the same time, should be adopted to improve job-shop operational performance.

Abstract
Work flows in a job-shop are determined not only by the release load but also by the number of accepted orders. In this paper the common assumption of accepting all incoming orders regardless of shop condition is relaxed. Instead of placing the orders in a 'pre-shop pool' queue, as in previous research, orders that arrive at the shop, when it is highly congested, may be immediately rejected or their due dates may be negotiated. This paper explores the idea of controlling the workload since the acceptance/rejection stage. A new acceptance/rejection rule is proposed, and tests are conducted to study the sensitivity of job-shop performance to different order acceptance parameters, like the tolerance of the workload limit and the due date extension acceptance. The effect of the negotiation phase on the job-shop performance is evaluated using a simulation model of a generic random job-shop that allow us to conclude that having a negotiation phase prior to rejection improves almost all workload performance measures. Different tolerances of the workload limit slightly affect the performance of the job-shop.

Abstract
Work flows in a job-shop are determined not only by the release load but also by the number of accepted orders. In this paper the common assumption of accepting all incoming orders regardless of shop condition is relaxed. Instead of placing the orders in a 'pre-shop pool' queue, as in previous research, orders that arrive at the shop, when it is highly congested, may be immediately rejected or their due dates may be negotiated. This paper explores the idea of controlling the workload since the acceptance/rejection stage. A new acceptance/rejection rule is proposed, and tests are conducted to study the sensitivity of job-shop performance to different order acceptance parameters, like the tolerance of the workload limit and the due date extension acceptance. The effect of the negotiation phase on the job-shop performance is evaluated using a simulation model of a generic random job-shop that allow us to conclude that having a negotiation phase prior to rejection improves almost all workload performance measures. Different tolerances of the workload limit slightly affect the performance of the job-shop.