Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem

Construction projects are characterized as projects with multi phases and activities, complex, unique, and have many different parties and stakeholders. Risks could appear at one or more of the construction project stages and may affect the achievement of project objectives. Therefore, one of the key elements in the planning phase of any project is the risk management process (RMP). This study attempts to understand the terminology of risk in general, risk management, and response to risk in particular. This study is mainly a review of thirty-eight studies that have been published between 1997 and 2020 that demonstrate the importance of the crucial phase of risk response from the risk management process and its impact on

The present work aimed to study the efficiency of thermal osmosis process for recovery of water from organic wastewater solution and study the factors affecting the performance of the osmosis cell. The driving force in the thermo osmosis cell is provided by a difference in temperature across the membrane sides between the draw and feed solution. In this research used a cellulose triacetate (CTA), as flat sheet membranes for treatment of organic wastewater under orientation membrane of active layer facing feed solution (FS) and draw solution (DS) is placed against the support layer.  The organic materials were phenol, toluene, xylene and BTX (benzene, toluene, and xylene) used as feed solution. The osmotic agent in draw solution was

The purpose of this work is to study the classification and construction of (k,3)-arcs in the projective plane PG(2,7). We found that there are two (5,3)-arcs, four (6,3)-arcs, six (7,3)arcs, six (8,3)-arcs, seven (9,3)-arcs, six (10,3)-arcs and six (11,3)-arcs. All of these arcs are incomplete. The number of distinct (12,3)-arcs are six, two of them are complete. There are four distinct (13,3)-arcs, two of them are complete and one (14,3)-arc which is incomplete. There exists one complete (15,3)-arc.

  The relationship between the vision of the scenario and the director is represented in the second search for new mechanisms and possibilities that possess the direct effect and synonyms of the vision of the scenario, so he works on investing them in achieving his ideas and visions with more effectiveness and flexibility to achieve creative potentials, without resorting to the installations and expressive structures themselves that have exhausted their meaning, and lost their luster due to Its prevalence and familiarity on the one hand, and its activation on the other hand to achieve modernity at the level of aromas, after the director takes a method or approach that has privacy and exclusivity, and based on the foregoing, getting

The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)