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 Algorithm had also been adapted and implemented, with better results than the Dynamic Programming Model. This paper presents another philosophy for solving the same problem, based on an Evolutionary Algorithm. This approach was implemented using an Object Oriented language, Java, and its results were compared to the Electromagnetism Algorithm. A distributed version was also developed, to be run in a computer network, in order to take advantage of available computational resources.
The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.
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ICOPEV2018 – 4th International Conference on Production Economics and Project Evaluation | 20 Set. - 21 Set. 2018
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This paper presents a systematic literature review about traditional, Agile and Lean Project Management methodologies. A general overview on the methodologies was also made, either on the perspective of the traditional based methodologies or the Lean and Agile methodologies. SLR results revealed more than 3500 papers. After filtering and applying exclusion criteria, just 80 were analysed. Main findings were that, in spite of some reserves, project management methodologies based on Lean are used. Nevertheless, Agile methodologies are the most used.
The expansion of textile and clothing production to Asian regions has both, increased competition and created a need for integration with the textile and clothing global supply chain. Strategies are being designed to improve competitiveness and responsiveness of the chains with increasing diversification of products. This study examines the potential of different strategies formulated by experts with focus on Pakistan s case, developed by brain storming sessions with external experts, composed from a chain s internal-view and based on existing strengths and weaknesses in the chain using a SWOT analysis. The aim of this previous study was to identify internal and external factors relevant to textile and clothing supply chain in Pakistan. These factors played an important role in the development of strategies which are useful for improving the competitiveness of the chain. In future it is our intention to formulate our decision structure based on external view of the chain and with more generalized criteria. This kind of structure produces the view which is usual in supply chain competitive scenarios. Here the criteria were viewed internally and the problem was formulated based on SWOT factors. Thus, using inputs from our previous work, “SWOT Analysis of Pakistan Textile Supply Chain”, we evaluated the strategies developed for achieving competitiveness in textile and clothing supply chain in Pakistan and their potential effects using a process of prioritization following Saaty s AHP. There can be innerdependencies and feedback within criteria, sub factors and alternatives which may have potential effects on the results. To study the effects of innerdependencies among factors we have used ANP and compared the results obtained by the two methods. We have suggested the implementation of developed strategies simultaneously through different entities involved with the chain, as government agencies, academic and research institutes, industrial associations and entrepreneurs themselves.
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Sustainability has become increasingly important. Existing project management methodologies are underdeveloped in sustainability. PM² is a methodology developed by the European Commission that aims to provide solutions and benefits to organizations. However, it doesn't include sustainability in its guide, because it aims to be generic. PRiSMTM aims to make the project management process more sustainable, it is based on the P5™ standard that aims to align portfolios, programmes and projects with sustainability. The major difference between the two methodologies is their main objectives. PRiSMTM has P5 Impact Analysis and Sustainability Management Plan as the main differentiating deliverable compared to other approaches, including PM². The most cited characteristic of PM² was to include best practices from other bodies of knowledge, and in PRiSMTM and P5™, it was to be an extension of the Triple Bottom Line, as it also includes product and process. The CEO of the PM² Alliance believes that PM² aims to be generic and usable for any project, so a focus on sustainability would remove the "elasticity" of the methodology. However, users wishing to use PM² and consider sustainability can include it in the additional objectives and use the P5 Impact Analysis and Sustainability Management Plan.
The project management field has shown great progress over the last decades. With technology evolution, project managers as well as other managers have a faster and more efficient way to handle information. While progress brought more abilities to managers, it also brought them more requirements, and an increasingly higher level of minimum accepted quality. The development and usage of new scheduling techniques became therefore imperative, so that better results could be achieved. In this research, four scheduling techniques well documented in the literature were studied: Early Start Schedule, Late Start Schedule, Constructive Heuristics and Branch-and-Bound. The main objective of this research project was to integrate these scheduling techniques into commercially available software, in order to help project managers deal with scheduling tasks in a more easy and controlled way. These scheduling techniques were integrated as an add-in, coded with C# programming language, for Microsoft Project 2010. After developing the add-in, an experimental phase was performed, in which the software was tested using some example projects. The initial hypothesis was confirmed by the results. For the tested projects the conclusion was that it was possible to get better results, concerning the project’s duration, using the studied techniques rather than the default scheduling technique used by Microsoft Project 2010.
We address the issue of optimal resource allocation, and more specifically, the analysis of complementarity of resources (primary resource or P-resource and resource or S-resource) to activities in a project. The concept of complementarity can be incorporated into the engineering domain as an enhancement of the efficacy of a primary resource (P-resource) by adding to it other supportive resources (S-resources). We developed a Genetic Algorithm capable of determining the ideal mixture of resources allocated to the activities of a project, such that the project is completed with minimal cost. This problem has a circularity issue that greatly increases its complexity. In this paper we present a constructive algorithm to build solutions from a chromosome that will be integrated in a Genetic Algorithm, which we illustrate by application to a small instance of the problem. The Genetic Algorithm is based on a random keys chromosome that is very easy to implement and allows using conventional genetic operators for combinatorial optimization problems. A project is formed by a set of activities. Each activity uses a specific set of resources, and it is also necessary to guarantee that there is no overlap in the time it takes to process activities in the same resource.
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In the past several years, various optimization algorithms had been implemented on the project total cost minimization problem. Lately, it was developed an application that serves as a central platform that integrates all those previous implementations. Currently, such platform allows the access and execution of each one of the other utilities as modules/plugins. Each of which can be configured to execute optimizations over different projects. Although the platform already saves the optimization results, it lacks a suitable processing mechanism that would ease the cross analysis over all the utilities. Therefore, we want to include capture and analysis of results into the platform in order to properly aggregate them in a results database. Such database could then be queried for numerous purposes being the performance evaluation, across the optimization utilities, one of the first. In this project we analyze a total of five heterogeneous optimization utilities, all coded in Java, using algorithms based on dynamic programming and global optimization. The heterogeneity poses a challenge which we overcame by establishing a common results storage language, by means of XML files.
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