BI-OBJECTIVE OPTIMIZATION FOR REBAR CUTTING PLAN USING SYMBIOTIC ORGANISMS SEARCH

Abstract

The construction industry is one of the biggest industries in the world. One of the most important materials in this industry is the reinforced steel bar. In construction site usually fabricated the reinforced steel bars into the form of one-dimensional stocks and designed according to the structural specification and installed in various structural components such as columns, beam, slab, and foundation. The purpose of cutting stock problems for reinforced steel bars (rebar cutting plan, RCP) is to satisfy the project requirements and also to minimize the cutting losses, which is the major contributor to the construction waste As there are two objective functions, we call the problem bi-objective rebar cutting plan (B-RCP). In the previous research, efforts developed the metaheuristics method to minimize the cutting losses in preliminary engineering designs but it few to consider about simplicity in order to achieve efficient work. Thus, this research applies the bi-optimization with epsilon constraint in order to find the trade-off solution between the material waste and number of cutting pattern for decision making. This study proposed the metaheuristic method Symbiotic Organisms Search (SOS) to solve B-RCP in one framework, to find the feasible cutting patterns along with the minimum total waste of the reinforced steel bar. To test the performance of the proposed SOS framework, the previous study case is set to be a benchmark, and then create a comparison with PSO. For real project instances of RCP are used to evaluate and validate the performance of SOS. The validation results from both cases of RCP show that SOS has better performance than PSO in both minimize the material waste along reducing the number of cutting patterns. Thus, it is validated that SOS is a competitive algorithm for solving the RCP.