Customer returns are a headache for businesses, especially in the world of online shopping. They cost money and time, but they can't be avoided. So, how can companies deal with this issue more effectively? One way is by tackling a specific problem: the multi-supplier closed-loop location-inventory problem, or CLLIP. This problem focuses on reducing overall supply chain costs by making smart decisions about where to place facilities and how to manage inventory. It's a complex puzzle, but a new solution might just be the key to cracking it.

The solution comes in the form of an improved hybrid artificial bee colony algorithm, or IHABC. This isn't your average algorithm. It's been enhanced with two new search equations that help it explore different solutions and refine them more effectively. Think of it like a bee buzzing around, checking out different flowers (solutions) and then zeroing in on the best ones. The goal is to find the most cost-effective strategies for the supply chain.

To see if IHABC is as good as it sounds, it was put to the test against other artificial bee colony algorithms and a commercial solver called Lingo. The results were impressive. IHABC consistently found better solutions faster. In fact, it achieved up to 29. 97% improvement in solution quality over the standard ABC algorithm. This means it could help businesses save a significant amount of money and time.

But the benefits don't stop at cost savings. IHABC also provides valuable insights. Through a sensitivity analysis, managers can gain a deeper understanding of how different factors affect their supply chain. This knowledge can guide strategic decisions, making supply chain operations more efficient and resilient.  The IHABC is a powerful tool for supply chain management. It offers a practical way to handle customer returns and optimize operations. By using this algorithm, businesses can make smarter decisions, save money, and stay competitive in a challenging market.

Solving the Return Conundrum: A Fresh Approach to Supply Chain Management

Actions