The focus of this paper is to explore and discuss the applicability of traditional operations management principles within the context of humanitarian service operations (HSO), illustrated by a nonprofit humanitarian service organization (HNPSO). We want to make two major contributions related to performance improvement based on lead time reduction and performance measurement. First, we develop an improvement framework to analyze and reduce the service lead time in parallel with provision of an improved capacity management. The results of this study show that lead time reduction strategies in combination with queuing theory based modeling techniques (Surf, 1998, 2002; Reiner, 2009) help the HNPSO managers effectively manage their service providing processes. Such an integrated and profound capacity management enables organization to deal with short-term demand fluctuations and long-term growth. In this way managers can find the balance between the provision of daily operations as well as the maintenance of monetary income to secure the growth of the organization and continuous improvement. Furthermore, we highlight the benefits and challenges of an aggregated performance measurement approach in a HNPSO. Our approach links operational, customer oriented, and financial performance measures, gives management competitive advantage more relevant than that of a traditional performance system. Considering the relatively limited operations management applications in nonprofit performance measurement systems, this paper contributes to both research and practice.

The basic principles of rapid modelling based on queueing theory, that provide the theoretical foundations for lead time reduction, are well known in research. We are globally observing an underinvestment in lead time reduction at top management levels. In particular, the maximization of resource utilization is still a wide-spread aim for managers in many companies around the world. This is due to inappropriate performance measurement systems as well as compensation systems for managers which neglect the monetary effects of lead time reduction. Therefore, we developed a model based on open queueing networks to evaluate the financial impacts of lead time reduction. Illustrated by an empirical case from the polymer industry, we will demonstrate the impact of performance measures on financial measures. That is why we will take into consideration efficiency performance measures (work in process, lead time, etc.) as well as effectiveness performance measure (e.g., customer satisfaction, retention rate). Based on our evaluation model, we will be able to investigate different scenarios to reduce lead time for the given case and evaluate these, based on the developed overall performance measurement model, i.e., optimization of the batch size, resource pooling, de/increase in the number of resources. In particular, we achieved a 75% lead time reduction and a 11% overall cost reduction (resource costs, setup costs, WIP costs, penalty costs, inventory costs) without changing the whole production layout or making high investments.

Trajectory data is of crucial importance for a vast range of applications involving analysis of moving objects behavior. Unfortunately, the extraction of relevant knowledge from trajectory data is hindered by the lack of semantics and the presence of errors and uncertainty in the data. This paper proposes a new analytical method to reveal the behavioral characteristics of moving objects through the representative features of migration trajectory patterns. The method relies on a combination of Fuzzy c-means, Subtractive and Gaussian Mixture Model clustering techniques. Besides, this method enables splitting the analysis into sections in order to differentiate the whole migration into i) migration-to-destination, ii) reverse-migration. The method also identifies places where moving objects' cumulate and increase in number during the moves (bottleneck points). It also computes the degree of importance for a given point or probability of existence of an object at a given coordinate within a certain confidence degree, which in turn determines certain zones having different degrees of importance for the move, i.e. critical zones of interest. As shown in this paper, other techniques are not capable to elaborate similar results. Finally, we present experimental results using a trajectory dataset of migrations of white storks (Ciconia ciconia).

This paper reviews the evolution of queueing networks software and its use in manufacturing. In particular, we will discuss two different groups of software tools. First, there are queueing networks software packages which require a good level of familiarity with the theory. In the other hand, there are some packages designed for manufacturing where the model development process is automated. Issues related to practical considerations will be adressed and recommendations will be given.

An assembly line is a production line in which units move continuously through a sequence of stations. The assembly line balancing problem is defined as the allocation of tasks to an ordered sequence of stations subject to precedence constraints with the objective of optimizing a performance measure. In this paper, we propose ant colony algorithms to solve the single-model U-type assembly line balancing problem. We conduct an extensive experimental study in which the performance of the proposed algorithm is compared against best known algorithms reported in the literature. The results indicate that the proposed algorithms display very competitive performance against them.