Existing theories and models in economics and transportation treat households’ decisions regarding allocation of time and income to activities as a resource-allocation optimization problem. Arguably, this stands in contrast with the dynamic nature of day-by-day activity-travel choices. Therefore, in the present paper we propose a different approach to model activity generation and allocation de...

In selecting tax returns for its examination program the IRS historically has focused primarily on direct revenue maximization. According to Plumley and Steuerle (2004), “The appeal of direct revenue maximization is that, for the most part, it is measurable, and it provides a basis for making resource allocation decisions.” However, Plumley and Steuerle (2004, page 329) also point out that by r...

Based on the GSM radio architecture, general packet radio service (GPRS) provides users data connections with variable data rates and high bandwidth efficiency. In GPRS service, allocation of physical channels is flexible, i.e., multiple channels can be allocated to a user. In this paper, we propose four algorithms for the GPRS radio resource allocation: fixed resource allocation (FRA), dynamic...

Resource management has been recognised as an important topic for the execution of business processes since long time ago. Yet, most exiting works on resource allocation have not paid enough attentions to process characteristics, such as structural and task dependencies. Furthermore, no effort has been made on optimising resource allocation by improving business processes. To address this issue...

Emerging large scale utility computing systems such as Grids promise computing and storage to be provided to end users as a utility. System management services deployed in the middleware are a key to enabling this vision. Utility Grids provide a challenge in terms of scale, dynamism, and heterogeneity of resources and workloads. In this paper, we present a model based architecture for resource ...

Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources. To provide cloud computing services economically, it is important to optimize resource allocation under the assumption that the required resource can be taken from a shared resource pool. In addition, to be able to provide processing ability and storage capacity, it...

Efficient and fair allocation of multiple types of resources is a crucial objective in a cloud/distributed computing cluster. Users may have diverse resource needs. Furthermore, diversity in server properties/capabilities may mean that only a subset of servers may be usable by a given user. In platforms with such heterogeneity, we identify important limitations in existing multi-resource fair a...

By considering a distributed system composed of a set of servers, clients, and resources, which characterize environments such as Grids or Clouds, we propose a distributed algorithm for resource allocation. It exploits fuzzy logic whenever a server, which cannot locally satisfy a client resource allocation request, needs to decide to which remote server the request should be forwarded. Furtherm...

The New York Police Department (NYPD) is tasked with responding to a wide range of incidents that are reported through the city’s 911 emergency hotline. Currently, response resources are distributed within police precincts on the basis of high-level summary statistics and expert reasoning. In this paper, we describe our first steps towards a better understanding of 911 call activity: temporal b...

In this paper, we present a genetic algorithm (GA) for optimization of a multi-mode resource constrained time cost trade off (MRCTCT) problem. The proposed GA, each activity has several operational modes and each mode identifies a possible executive time and cost of the activity. Beyond earlier studies on time-cost trade-off problem, in MRCTCT problem, resource requirements of each execution mo...