The MABAC method using for supply chain management based on the bipolar complex fuzzy soft hamacher aggregation operators

In real life, we can face many things and services, which are performed regularly. Supply Chain Management (SCM) is the one that does the business. SCM refers to the management of finished products and their distribution to the final consumer. Many types of services relieve people a lot and create a lot more attachment with people. Online services are very easy for those people who cannot afford to buy equipment from cities. From this, they saved a large part of all processing income and time. The use of bipolar complex fuzzy soft sets (BCFSS) in SCM is investigated in this research. The bipolar complex fuzzy soft Hamacher weighted average (BCFSHWA), bipolar complex fuzzy soft Hamacher ordered weighted average (BCFSHOWA), bipolar complex fuzzy soft Hamacher hybrid average (BCFSHHA), bipolar complex fuzzy soft Hamacher weighted geometric (BCFSHWG), bipolar complex fuzzy soft Hamacher ordered weighted geometric (BCFSHOWG), and bipolar complex fuzzy soft Hamacher hybrid geometric (BCFSHHG) are among the operators that we present and illustrate. We utilize these operators to address bipolar complex fuzzy soft Multi-Attribute Border Approximation area Comparison (MABAC) issues and analyze their specific instances. We illustrate the efficacy and superiority of our technique over current methods using a numerical example in SCM, highlighting its potential for attaining optimal performance and solutions in SCM scenarios.