Multi-objective genetic optimization for scheduling a multi-storey building

Multi-objective optimization problems can be found in various fields, however, optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. This paper proposes developed Genetic Algorithms (GAs) that enabled multi-objective optimization for scheduling a multi-storey building. However, a trade-off between time and cost for habitation projects is required to face limited fund and increasing population environment. This problem has an important position for developing countries' governments because it's related to low cost habitation projects. Multi-storey buildings are classified as special repetitive projects because of skeleton constraints. Activities can be classified into: repetitive and non-repetitive ones. The present model enables construction planners to direct controlled time-cost construction plan by investigating optimal plans, generated from a set of feasible alternatives, which minimize project duration, total number of crews, and total work interruptions. This model satisfies the following aspects: 1) it is based on the line of balance technique; 2) it considers non-serial typical activity networks with finish-start relationship and both lag and overlap time between activities are allowed; 3) it utilizes a tool to identify activities in a typical repeated floor; and 4) it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of a multi-storey building. (C) 2014 Elsevier B.V. All rights reserved.