Abstract
This work deals with the application of artificial intelligence instruments in a building schedule. In this article there was presented an original optimization scatter search algorithm taking into consideration both technological and organizational restrictions. This algorithm was applied to the real analysis of the industrial building project realization.
Highlights
Optimal scheduling of construction projects is an important task as it influences the effectiveness of executive companies in a crucial way
Optimization of realization process presented on the example of the construction works and models of works consists in a certain problem of tasks arrangement on machines, so-called permutational flow shop problem with a costs delay sum minimization
This paper provides a practical scatter search algorithm for the total weighted tardiness flow shop problem, as a mathematical model of construction project management
Summary
Optimal scheduling of construction projects is an important task as it influences the effectiveness of executive companies in a crucial way. Optimization of realization process presented on the example of the construction works and models of works consists in a certain problem of tasks arrangement on machines, so-called permutational flow shop problem with a costs delay sum minimization. The production process optimization consists in fixing such an order of elements manufacturing that it would provide us with optimal results measured by value of a certain criterion (e.g. a sum of penalties for a delay) It can be usually made by defining a combinatorial problem in which the optimal element should be determined (a sequence or a permutation) in a definite, usually very big set of acceptable solutions. Presented in the previous chapters issues connected with optimization of certain building projects’ realization (in the language of scheduling tasks theory) can be defined as a problem of determining of the optimal sequence of tasks’ realization on machines, and at the same time the costs delay sum of tasks constitutes the optimization criterion. It’s noticeable while solving instances with many numbers of tasks
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