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In this article, a multi-objective scheduling optimization model using Genetic Algorithms is proposed to minimize makespan (maximum completion time), total tardiness and total earliness simultaneously. Many other objectives like maximum tardiness, maximum earliness, and a minimum number of tardy jobs can be optimized easily using the proposed model. The model has been carried out using the MS Excel spreadsheets and an add-in to provide the GA which is known as Evolver. A set of projects has been used to examine the model and its effectiveness has been proven. The proposed model is more flexible than other existing software with superior performance and accurate results comparing with what is obtained for others like LEKIN.

Objectives:The research aims at minimizing construction projects' costs, including solid slab materials (steel and concrete), by analyzing the slab's parameters and optimizing the slab design using the iteration method. Methods: Research data were given as thirty solid slabs. Excel spreadsheets were made according to the Saudi Building Code specifications to optimize the slab design automatically and determine the minimum amount of concrete and steel. Plugging of the given data was done in an iterated method while assuring that outputs are within the allowable limits till reaching the possible optimum design. Findings: Study results reveal that slab 4 and slab 5 have the lowest calculated cost ($7,825.33/m^2) even though they have different amounts of concrete and steel. The two parameters, the actual depth of the slab and the steel bar' diameters, played a significant role in slab cost reduction. It is recommended that slabs from (20) to (30) be designed as flat slabs due to the chance to increase concrete instead of the steel amount. Novelty: The study utilized the iteration method in construction cost optimization, which the previous studies related to the topic field had not used.

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