We consider the problem of allocating resources to projects performed under given due dates and stochastic time–cost tradeoff settings. In particular, we show how to implement a state-of-the-art methodology known as “robust optimization” to solve the problem. In contrast to conventional approaches, the model we develop results in management policies rather than optimal values for the original d...

Project planner’s main goal is to complete project with minimal time as well as minimal cost. Much effort (e.g. resources which demand cost) is required to complete the project in shorter time. There is a trade-off relationship between activity duration and its resources. This study employed a GA based multi-objective approach for time-cost tradeoff using resources-time tradeoff as input. Combi...

Maintenance strategies are typically implemented by optimizing only the cost whilst the reliability of facility performance is neglected. This study proposes a novel algorithm using multi-objective particle swarm optimization (MOPSO) technique to evaluate the cost-reliability tradeoff in a flexible maintenance strategy based on non-dominant solutions. Moreover, a probabilistic model for regress...

Tradeoff between time and cost is an important issue in planning a project. This paper deals with a stochastic Time-Cost Tradeoff Problem (TCTP) in PERT network of project management. All activities are subject to linear cost function and assumed to be exponentially distributed. The aim of this problem is to maximize the project completion probability with a pre-known deadline to a predefined p...

We present BlowFish, a distributed data store that admits a smooth tradeoff between storage and performance for point queries. What makes BlowFish unique is its ability to navigate along this tradeoff curve efficiently at finegrained time scales with low computational overhead. Achieving a smooth and dynamic storage-performance tradeoff enables a wide range of applications. We apply BlowFish to...

Cryptanalytic time memory tradeoff algorithms are generic one-way function inversion techniques that utilize pre-computation. Even though the online time complexity is known up to a small multiplicative factor for any tradeoff algorithm, false alarms pose a major obstacle in its accurate assessment. In this work, we study the expected pre-image size for an iteration of functions and use the res...

A fundamental question in learning theory is the quantification of the basic tradeoff between the complexity of a model and its predictive accuracy. One valid way of quantifying this tradeoff, known as the “Information Bottleneck”, is to measure both the complexity of the model and its prediction accuracy by using Shannon’s mutual information. In this paper we show that the Information Bottlene...

Distributed Constraint Optimization (DCOP) is a key technique for solving agent coordination problems. Because finding cost-minimal DCOP solutions is NP-hard, it is important to develop mechanisms for DCOP search algorithms that trade off their solution costs for smaller runtimes. However, existing tradeoff mechanisms do not provide relative error bounds. In this paper, we introduce three trade...