Construction contractors usually undertake multiple construction projects simultaneously. Such a situation involves sharing different types of resources, including monetary, equipment, and manpower, which may become a major challenge in many cases. In this study, the financial aspects of working on multiple projects at a time are addressed and investigated. The study considers dealing with financial shortages by proposing a multi-project scheduling optimization model for profit maximization, while minimizing the total project duration. Optimization genetic algorithm and finance-based scheduling are used to produce feasible schedules that balance the finance of activities at any time with the available funds. The model has been tested in multi scenarios, and the results are analyzed. The results show that negative cash flow is minimized from −693,784 to −634,514 in enterprise I and from −2,646,408 to −2,529,324 in enterprise II in the first scenario and also results show that negative cash flow is minimized to −612,768 with a profit of +200,116 in enterprise I and to −2,597,290 with a profit of +1,537,632 in enterprise II in the second scenario.
Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex
<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T
... Show MoreIn the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show MoreThis paper include the problem of segmenting an image into regions represent (objects), segment this object by define boundary between two regions using a connected component labeling. Then develop an efficient segmentation algorithm based on this method, to apply the algorithm to image segmentation using different kinds of images, this algorithm consist four steps at the first step convert the image gray level the are applied on the image, these images then in the second step convert to binary image, edge detection using Canny edge detection in third Are applie the final step is images. Best segmentation rates are (90%) obtained when using the developed algorithm compared with (77%) which are obtained using (ccl) before enhancement.
In gene regulation, transcription factors (TFs) play a key function. It transmits genetic information from DNA to messenger RNA during the process of DNA transcription. During this step, the transcription factor binds to a segment of the DNA sequence known as Transcription Factor Binding Sites (TFBS). The goal of this study is to build a model that predicts whether or not a DNA binding site attaches to a certain transcription factor (TF). TFs are regulatory molecules that bind to particular sequence motifs in the gene to induce or restrict targeted gene transcription. Two classification methods will be used, which are support vector machine (SVM) and kernel logistic regression (KLR). Moreover, the KLR algorithm depends on another regress
... Show MoreTraffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho
... Show More In this paper,we construct complete (kn,n)-arcs in the projective plane PG(2,11), n = 2,3,…,10,11 by geometric method, with the related blocking sets and projective codes.
A (k,n)-arc is a set of k points of PG(2,q) for some n, but not n + 1 of them, are collinear. A (k,n)-arc is complete if it is not contained in a (k + 1,n)-arc. In this paper we construct complete (kn,n)-arcs in PG(2,5), n = 2,3,4,5, by geometric method, with the related blocking sets and projective codes.
The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca