Labro, Eva; Vanhoucke, Mario (Vlerick Business School, 2005)
The academic accounting literature has established that the conditions under which costing systems in general and Activity Based Costing (ABC) in particular provide accurate costs are very stringent. Less is known, however, about the nature, level and bias of costing errors and their interactions, when these conditions are not met. The main problem to overcome to enable us to learn about these is the notion of the unobservable true cost benchmark to which to compare the costing system approximation. This paper presents a simulation method to deal with this problem, allowing a variety of research questions in this research area to be addressed with more generalizable answers. Using our methodology, we test a variety of hypotheses on the interaction between various errors in costing system design that were developed in the previous analytical, empirical, and practitioner literature. We also provide some interesting new insights on interactions between errors that were previously not discussed in the literature. This paper presents new results on (1) conditions under which partial refinement in costing systems does or does not work to improve overall accuracy, (2) the contexts in which it is most effective to correct a particular type of error in terms of improving overall accuracy and (3) indicators of robustness or sensitivity of costing system designs to errors. In doing so, we also provide insights relevant to practitioners, costing system designers and users of costing information alike. Keywords: costing system design, costing accuracy, simulation, costing errors
This paper describes a detailed study of a recursive search algorithm for different optimization problems. Although the algorithm has been originally developed for a project scheduling problem with financial objectives, we show that it can be extended to many other application areas and therefore, can serve as a sub-procedure for various optimization problems. The contribution of the paper is threefold. First, we present a hybrid recursive search procedure for the project scheduling problem with net present value maximization and compare it with state-of-the-art procedures by means of computational tests. Second, we show how the procedure can be adapted to two other application areas: project scheduling with work continuity minimization and the open pit mining problem. Last, we highlight some future research areas where this hybrid procedure might bring a promising contribution.
Maenhout, Broos; Vanhoucke, Mario (Vlerick Business School, 2005)
In this paper, we present a novel meta-heuristic technique for the nurse scheduling problem (NSP). This well-known scheduling problem assigns nurses to shifts per day taking both hard and soft constraints into account. The objective is to maximize the preferences of the nurses and to minimize the total penalty cost from violations of the soft constraints. The problem is known to be NP-hard. Due to its complexity and relevance, many algorithms have been developed to solve practical, and often case-specific versions of the NSP. The enormous amount of different constraints has led to an overwhelming amount of exact and meta-heuristic procedures, and hence comparison and state-of-the-art reporting of standard results seem to be a utopian idea. The contribution of this paper is twofold. First, we present a meta-heuristic procedure for the NSP based on the framework proposed by Birbil and Fang (2003). The Electromagnetic (EM) approach is based on the theory of physics, and simulates attraction and repulsion of sample points in order to move towards a promising solution. Second, we present computational experiments on a standard benchmark dataset, and solve problem instances under different assumptions. We show that our procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints. Keywords: meta-heuristics, electromagnetism, nurse scheduling
Vanhoucke, Mario; Vandevoorde, Stephan (Vlerick Business School, 2005)
It is well-known that well managed and controlled projects are more likely to be delivered on time and within budget. The construction of a (resource-feasible) baseline schedule and the follow-up during execution are primary contributors to the success or failure of a project. Earned value management systems have been set up to deal with the complex task of controlling and adjusting the baseline project schedule during execution. Although earned value systems have been proven to provide reliable estimates for the follow-up of cost performance, it often fails to predict the total duration of the project. In this paper, we extensively review the existing methods to forecast the total project duration. Moreover, we investigate the potential of a newly developed method, the earned schedule method, which makes the connection between earned value metrics and the project schedule. We present an extensive simulation study where we carefully control the level of uncertainty in the project, the influence of the project network structure on the accuracy of the forecasts, and the time horizon where the newly developed measures provide accurate and reliable results. Keywords: Earned value, earned duration, earned schedule, CPM
In this paper, we present a meta-heuristic algorithm for the well-known resource-constrained project scheduling problem with discounted cash flows. This optimization procedure maximizes the net present value of project subject to the precedence and renewable resource constraints. The problem is known to be NP-hard. We investigate the use of a enhanced bi-directional generation scheme and a recursive forward/backward improvement method and embed them in a meta-heuristic scatter search framework. We generate a large dataset of project instances under a controlled design and report detailed computational results. The solutions and project instances can be downloaded from a website in order to facilitate comparison with future research attempts. Keywords: Resource-constrained project scheduling, Net present value, Scatter search
We present a finite capacity production scheduling algorithm for an integrated steel company located in Belgium. This multiple-objective optimization model takes various case-specific constraints into account and consists of two steps. A machine assignment step determines the routing of an individual order through the network while a scheduling step makes a detailed timetable for each operation for all orders. The procedure has been tested on randomly generated data instances that reflect the characteristics of the steel company. We report promising computational results and illustrate the flexibility of the optimization model with respect to the various input parameters. Keywords. Master production scheduling, manufacturing planning and control, scheduling/sequencing.
Boute, Robert; Disney, Stephen M.; Van Mieghem, Jan A. (2019)
We investigate the emerging trend of near-shoring a small part of the global production to local SpeedFactories. The short lead time of the responsive SpeedFactory reduces the risk of making large volumes in advance, yet it does not involve a complete re-shoring of demand. Using a break-even analysis we investigate the lead time, demand, and cost characteristics that make dual sourcing with a SpeedFactory desirable compared to complete off-shoring. We propose order rules that extend the celebrated inventory optimal order-up-to replenishment policy to settings where capacity costs exist and demonstrate their excellent performance. We highlight the significant impact of autocorrelated and non-stationary demand series, which are prevalent in practice yet challenging to analyze, on the economic benefit of re-shoring. Methodologically, we adopt Z-transforms and present exact analyses of several discrete-time linear production-inventory models.
Vereecke, Ann; Pandelaere, Els (Vlerick Business School, 2004)
Since the introduction of the concepts of lean manufacturing, agility and mass customization it is questioned to what extent the trade-off between cost and flexibility still holds. It has been the objective of our research to test the trade-off theory empirically using the data of the International Manufacturing Strategy Survey (IMSS). Our research confirms the well accepted manufacturing profile of low cost producers, which typically use a line process, and of flexible producers, which typically produce in a job shop. However, we also observe that some companies manage to overcome the cost/flexibility trade-off, by introducing the concept of postponed manufacturing. These companies are characterized by an assembly-to-order policy of standardized semi-finished products, produced in a line process. Flexibility and low cost are thus obtained by playing with the position of the decoupling point. Keywords: manufacturing strategy, mass customization, flexibility
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