Basic approximations to an adaptive resource allocation technique to stochastic multimodal projects

This paper presents three basic approximations developed to solve the Adaptive Stochastic Multimodal Resource Allocation Problem. Two of them are based on the DP model introduced in earlier papers ([23], [24]). The other one uses NLP to solve this problem. The approximations developed consist in considering the Work Content of some or all the activities of the project as represented by their mean values. These approximations were applied to a set of examples, and results were obtained and commented. As expected, running times were reduced, compared to the original model, but the total cost was underestimated, due to the use of means instead of the complete distribution

Adaptive resource allocation in multimodal activity networks

In practice, project managers must cope with uncertainty, and must manipulate the allocation of their resources adaptively in order to achieve their ultimate objectives. Yet, treatments of the well-known ‘resource constrained project scheduling problem’ have been deterministic and static, and have addressed mostly unimodal activities. We present an approach to resource allocation under stochastic conditions for multimodal activity networks. Optimization is via dynamic programming, which proves to be demanding computationally. We suggest approximation schemes that do not detract signi…cantly from optimality, but are modest in their computational requirements

The optimal resource allocation in stochastic activity networks via the electromagnetism approach

An optimal resource allocation approach to stochastic multimodal projects had been previously developed by applying a Dynamic Programming model, which proved to be very demanding computationally. Approximations to the initial model had been also developed, still within DP framework. Computing times were improved, but demonstrated the need for further developments. In this paper we report on the application of a recently developed technique for global optimization, the Electromagnetism Algorithm (EMA), to this problem and demonstrate its superior performance to previously attempted approximations

Experimental results of an adaptive resource allocation

We describe the structure and the implementation aspects of the dynamic programming procedure that was proposed in a previous report (Tereso et al., 2001) for the optimal resource allocation to activities under the assumption of stochastic work content. We illustrate its implementation to five projects of varying size, which exhibit the computational complexity of the procedure. The pseudo-code may be obtained by request from the lead author

On the optimal resource allocation in projects considering the time value of money

The optimal resource allocation in stochastic activity networks had been previously developed by applying three different approaches: Dynamic Programming (DP), an Electromagnetism Algorithm (EMA) and an Evolutionary Algorithm (EVA). This paper presents an extension to the initial problem considering the value of money over time. This extended problem was implemented using the Java programming language, an Object Oriented Language, following the approaches previously used (DP, EMA and EVA).Fundação para a Ciência e a Tecnologia (FCT

Quantity oriented resource allocation strategy on multiple resources projects under stochastic conditions

Previous developments from the first author and other researchers were made on devising models for the total cost optimization of projects described by activity networks under stochastic conditions. Those models only covered the single resource case. The present paper will discuss the case of multiple resources. More precisely, we introduce a strategy of allocation of those resources in order to minimize the waste arising from their latent idleness on their consumption within the same activity. On this strategy we elect one resource as “pivot” and write equations that describe all the quantities for the other resources, on the same activity.Fundação para a Ciência e a Tecnologia (FCT

Project management: multiple resources allocation

Given a project network under stochastic conditions, the goal is to determine the optimal resource allocation to the activities in order to minimize the total project cost. This cost includes the resource cost and the tardiness cost. In this work we consider the multiple resources case, which is an extension of the models previously developed by the rst author and other researchers, considering a single resource. We assume that all the resources are independent and abundant. The work consists mainly of two parts: formalization of the new models, and their implementation in Java. In order to formalize the models, it was necessary to establish an allocation strategy for the multiple resources. This is required to ensure the desired equality of expected durations yielded by each resource in the same activity. We study four di erent allocation strategies: two of them are derived from the stochastic nature of the work content by equalizing the expected durations, thus determining the allocation vectors; and the other two go down to the level of all possible values to devise an allocation method (among all the allocation vectors, selects those leading to equal expected durations). Then the probability distributions of the variables required for analysis and evaluation were determined. Although the research has covered four strategies, one proved to be inferior compared to the others, and another was too complex to be easily implemented. The remaining two are strong rivals with neither dominating the other, and one of them was arbitrarily chosen for implementation. The implementation covers three algorithms: Dynamic Programming Algorithm, Electromagnetic Algorithm and Evolutionary Algorithm. Concurrent programming was exploited to enhance performance. We report on the performance of our application over a representative set of project networks.Fundação para a Ciência e a Tecnologia (FCT

Duration oriented resource allocation strategy on multiple resources projects under stochastic conditions

Previous developments from the first author and other researchers were made on devising models for the total cost optimization of projects described by activity networks under stochastic conditions. Those models only covered the single resource case. The present paper will discuss the case of multiple resources. More precisely, we introduce a strategy of allocation of those resources in order to minimize the waste arising from their latent idleness on their consumption within the same activity. With this strategy we will start from the possible durations yielded by each resource and devise the allocation vector leading to equal durations.Fundação para a Ciência e a Tecnologia (FCT

Optimal resource allocation in stochastic activity networks via the electromagnetism approach: a platform implementation in Java

An optimal resource allocation approach to stochastic multimodal projects had been previously developed by applying a Dynamic Programming model which proved to be very demanding computationally. A new approach, the Electromagnetism-like Mechanism, has also been adopted and implemented in Mat lab, to solve this problem. This paper presents the implementation of the Electromagnetism approach using an Object Oriented language, Java, and a distributed version to be run in a computer network, in order to take advantage of available computational resources.info:eu-repo/semantics/publishedVersio