Service level

About: Service level is a research topic. Over the lifetime, 7647 publications have been published within this topic receiving 126093 citations. The topic is also known as: service level.

Designing urban transit systems : an approach to the route-technology selection problem

Abstract: The service specification model is a tool for generating and screening public transportation systems during the initial planning stages. It is based on the concept of a service specification or supply function that integrates hardware system attributes and operating policy. A service specification is an integrated set of statements that defines which hardware-headway combination is to be used for any level of flow across a link. Walk mode may be included in the specification. The model defines a transit system within a network which includes all potential and existing transit links. The current model assumes that transit demand is known. The mechanism of the model is an iterative assignment procedure that is similar to the capacity restraint model. The template network is started at the "best" hardware-headway service level. Link service levels are iteratively adjusted to correspond to link flow level as specified by the service specification. The iterative process ends when no further changes in link service level are required. Empirical tests show that the model is sensitive to the policy decisions and hardware mix incorporated in the service specification and to the size and orientation of the transit demand. The attainment of an equilibrium flow distribution appears to be influenced by the form of the service specification, the percentage of nonplanar links, and the presence of fixed transit-time links in the template network. The model appears to be a useful tool for generating alternative transport system configurations based on different technology mixes and operating policies in any transportation context for which a service specification can be formulated.

Inventory Pooling to Deliver Differentiated Service

Abstract: Inventory pooling is at the root of many celebrated ideas in operations management. Postponement, component commonality, and resource flexibility are some examples. Motivated by our experience in the aftermarket services industry, we propose a model of inventory pooling to meet differentiated service levels for multiple customers. Our central research question is the following: What are the minimum inventory level and optimal allocation policy when a pool of inventory is used in a single period to satisfy individual service levels for multiple customers? We measure service by the probability of fulfilling a customer’s entire demand immediately from stock. We characterize the optimal solution in several allocation policy classes; provide some structural results, formulas, and bounds; and also make detailed interpolicy comparisons. We show that the pooling benefit is always strictly positive, even when there are an arbitrary number of customers with perfectly positively correlated demands.

Risk management in liner ship fleet deployment: a joint chance constrained programming model

Abstract: This paper provides a tangible methodology to deal with the liner ship fleet deployment problem aiming at minimizing the total cost while maintaining a service level under uncertain container demand. The problem is first formulated as a joint chance constrained programming model, and the sample average approximation method and mixed-integer programming are used to deal with it. Finally, a numerical example of a liner shipping network is carried out to verify the applicability of the proposed model and solution algorithm. It is found that the service level has significant effect on the total cost.

Implanting the benefits of buyer‐supplier collaboration in the soft fruit sector

Abstract: Purpose – The paper aims to show how a collaborative approach to demand management can improve customer service to the benefit of both supermarkets and suppliers in sectors characterised by volatile consumer demand.Design/methodology/approach – This insight paper is based on face‐to‐face interviews conducted with key representatives from the two businesses involved, to gain insight into the nature of the problem, the approach adopted and the benefits achieved.Findings – Supermarket buyers have neither the time nor the capability to manage demand effectively at store level, resulting in excessive waste and lost sales, which hurt both the supermarket and their suppliers. Giving access to internal demand management systems to trusted suppliers can have significant impacts on service levels and supply chain performance.Research limitations/implications – The insights presented are specific to one supermarket supply chain but the lessons are generic.Practical implications – The paper demonstrates the impact wh...

Self-Adaptive and Resource-Efficient SLA Enactment for Cloud Computing Infrastructures

Abstract: Cloud providers aim at guaranteeing Service Level Agreements (SLAs) in a resource-efficient way. This, amongst others, means that resources of virtual (VMs) and physical machines (PMs) have to be autonomically allocated responding to external influences as workload or environmental changes. Thereby, workload volatility (WV) is one of the crucial factors that influence the quality of suggested allocations. In this paper we devise a novel approach for self-adaptive and resource-efficient decision-making considering the three conflicting goals of minimizing the number of SLA violations, maximizing resource utilization, and minimizing the number of necessary time- and energy-consuming reconfiguration actions. We propose self-adaptive rule-based knowledge management for autonomic VM reconfiguration considering the rapidness of changes in the workload, i.e., WV. We introduce a novel WV categorization and present cost and volatility based methods for self-tuning. We evaluate these methods by a large variety of synthetically generated workloads, and by real-world measurements gathered from an image rendering application and a scientific workflow for RNA sequencing. Evaluation shows that in most cases the self-adaptive approach outperforms the static approach.