Reallocation of beds to reduce waiting time for cardiac surgery

Waiting time for cardiac surgery is a significant problem in the current medical world. The fact that patients length of stay varies considerably makes effective hospital operation a hard job. In this paper, the patients length of stay is analyzed. Three scenarios for hospital management are presented and evaluated in two ways. First, the theoretical number of beds needed in each of these scenarios is analyzed using techniques from Markov chain theory. This analysis does not include the important variability in length of stay. Therefore, the second evaluation is based on simulation experiments to further investigate the variability. The aim of the analyses is to look at unused bed capacity in the hospital wards. By knowing the size of the unused bed capacity, it is possible to come to a more efficient reallocation of the beds. The results presented in this paper provide some insight in the relation between patients length of stay, bed availability and hospital waiting lists. Finally, some ideas are raised as discussion points for further research.

Operational performance of two-stage food production systems : process interactions and capacitated storage

The food sector has seen several important developments in recent years. First, competition has become fiercer because of the increased market power of food retailing. Secondly, quality legislation has become more stringent due to a growing concern for food safety throughout the society. Third, sustainable production has become more important, and organizations are held responsible for the environmental performance of their production system. In this thesis, several aspects of these developments are studied from an Operations Management perspective. Specific questions that are addressed are: * What are the implications of capacity- and time-constrained intermediate storage on production performance? * What are the performance implications of demand characteristics like high product mix variability and lead time reductions? * How do planning decisions and process configurations influence the realization of product losses The results provide insight in the operational performance of two-stage food production systems with intermediate storage. This performance not only entails competitiveness (through the insights on lead time performance), but also sustainability (through the insight in realization of product losses).

Testing improvements in the chocolate traceability system: Impact on product recalls and production efficiency

The primary aim of food traceability is to increase food safety, but traceability systems can also bring other benefits to production systems and supply chains. In the literature these benefits are extensively discussed, but studies that quantify them are scarce. In this paper we propose two hypothetical improvements of the traceability system within the chocolate production system and supply chain and we illustrate the resulting benefits by using a case study. Based on the case study, we quantify the influence of these improvements on production efficiency and recall size in case of a safety crisis by developing a simulation tool. These results are aimed to illustrate and quantify the additional benefits of traceability information, and could help food industries in deciding whether and how to improve their traceability systems

MILP approaches to sustainable production and distribution of meal elements

This paper studies the production and distribution system forprofessionally prepared meals, in which a new innovative concept is applied. Theconcept aims to improve the sustainability of the system by distributing mealelements super-chilled in the conventional cold chain. Here, sustainabilitycomprises economic, environmental and social aspects. The impacts on andtrade-offs between the different dimensions of sustainability are discussed, andcombined with aspect of product quality. Furthermore, we identify the importantplanning decisions in relation to production and distribution and organisethese in a decision hierarchy. Based on these discussions, decision supportmodels based on mixed-integer linear programming are developed for the planningtasks on the tactical level, including decision-making on packaging options anddelivery structures. The resulting models can be used to support production anddistribution planning, and also evaluate the performance of and quantify thetrade-offs between the different sustainability dimensions.</p

Optimizing chocolate production through traceability: A review of the influence of farming practices on cocoa bean quality

Due to recent developments in traceability systems, it is now possible to exchange significant amounts of data through food supply chains. Farming practices applied by cocoa farmers at the beginning of the chocolate supply chain strongly influence several quality parameters of the finished chocolate. However, information regarding these practices does not normally reach the chocolate manufacturer. As a consequence, many specifications of the raw material cannot be taken into consideration in the operational decision making processes related to chocolate production. In recent years many studies have been investigating the influence of certain farming practices on cocoa beans and the subsequent chocolate quality parameters. However, no comprehensive analysis of the process variables in the chain and their effects on the quality can be found. In this paper we review and classify the available literature on the topic in terms of process variables throughout the chain, and their effects on quality and flavour aspects of cocoa beans and the eventual chocolate product. After analyzing the literature, we are able to identify potential benefits of using data regarding the farming practices into the chocolate production process. These potential benefits especially concern product quality and production yield, giving directions for the future of chocolate production

Scheduling cross-docking operations under uncertainty: A stochastic genetic algorithm based on scenarios tree

A cross-docking terminal enables consolidating and sorting fast-moving products along supply chain networks and reduces warehousing costs and transportation efforts. The target efficiency of such logistic systems results from synchronizing the physical and information flows while scheduling receiving, shipping and handling operations. Within the tight time-windows imposed by fast-moving products (e.g., perishables), a deterministic schedule hardly adheres to real-world environments because of the uncertainty in trucks arrivals. In this paper, a stochastic MILP model formulates the minimization of penalty costs from exceeding the time-windows under uncertain truck arrivals. Penalty costs are affected by products' perishability or the expected customer’ service level. A validating numerical example shows how to solve (1) dock-assignment, (2) while prioritizing the unloading tasks, and (3) loaded trucks departures with a small instance. A tailored stochastic genetic algorithm able to explore the uncertain scenarios tree and optimize cross-docking operations is then introduced to solve scaled up instaces. The proposed genetic algorithm is tested on a real-world problem provided by a national delivery service network managing the truck-to-door assignment, the loading, unloading, and door-to-door handling operations of a fleet of 271 trucks within two working shifts. The obtained solution improves the deterministic schedule reducing the penalty costs of 60%. Such results underline the impact of unpredicted trucks’ delay and enable assessing the savings from increasing the number of doors at the cross-dock