Constructability practice and project delivery processes in the Nigerian construction industry

As projects are getting complex by the day and for the fact that project failures – project abandonment, collapsed structures are constant discourse in the Nigerian news media, the need for constructability becomes very crucial in order to achieve project success. This study is aimed at investigating and analyzing the implementation of constructability in project delivery process in the Nigerian construction industry using Rivers State, Nigeria as a case study. Data was collected through questionnaire and interview approach. Results of data analyzed revealed that although a high percentage of the sampled population are familiar with the term “constructability”, nearly all do not have corporate constructability implementation manual nor apply formal constructability implementation programs and techniques as obtained in more developed countries. Constructability implementation is therefore neither systematic nor comprehensive in virtually all the firms surveyed. The universal principles of constructability were accepted by the professionals and rated in the order of importance. The most critical was identified as the carrying out of thorough investigation of site and development of a project plan. Conditions that constrain constructability in the opinion of the professionals were also identified and rated in the order of impact. Spearman rank correlation analysis revealed an agreement of opinion between different respondent groups in the sampled population. Engineers, project managers and other industry practitioners are enjoined to adopt these principles in their planning, design and construction activities in order to improve the overall project performance and achieve best practices in the industry

Application of Evolutionary Algorithms in Project Management

Part 7: Genetic AlgorithmsInternational audienceThe paper deals with “resource leveling optimization problems”, a class of problems that are often met in modern project management. The problems of this kind refer to the optimal handling of available resources in a candidate project and have emerged, as the result of the even increasing needs of project managers in facing project complexity, controlling related budgeting and finances and managing the construction production line. For the effective resource leveling optimization in problem analysis, evolutionary intelligent methodologies are proposed. Traditional approaches, such as exhaustive or greedy search methodologies, often fail to provide near-optimum solutions in a short amount of time, whereas the proposed intelligent approaches manage to quickly reach high quality near-optimal solutions. In this paper, a new genetic algorithm is proposed for the investigation of the start time of the non-critical activities of a project, in order to optimally allocate its resources. Experiments with small and medium size benchmark problems taken from publicly available project data resources, produce highly accurate resource profiles. The proposed methodology proves capable of coping with larger size project management problems, where conventional techniques like complete enumeration is impossible, obtaining near-optimal solutions