[2309.13218] Language Models for Business Optimisation with a Real World Case Study in Production Scheduling

View a PDF file from the paper entitled Linguistic Models to improve business with a real case study in scheduling, by Pivathuru Thejan Amarasinghe and 2 other authors

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a summary:Business improvement has been widely used to define optimal solutions to challenge commercial operations. Drafting problems is an important part of improving business because it affects the health of solutions and the efficiency of the improvement. While different improvement languages ​​have been developed, problem drafting is still not a trivial task and usually requires improvement experience and knowledge of problems. Recently, LLMS models have shown great performance through various language tasks. Since the formulation of problems can be considered a translation task, there is the ability to benefit from LLMS to automate the formulation of problems. However, the LLM development to formulate problems is a challenge, due to the limited training data, and the complexity of improvement problems in the real world. Several rapid engineering methods are suggested in literature to automate the formulation of problems with LLMS. While the initial results are encouraging, it is still possible to significantly improve the accuracy of these methods. In this paper, we present a LLM standing framework to automate the formulation of problems in improving business. Our approach provides a way to adjust the cost -cost LLMS The results of the experiment shows that our framework can generate accurate installations of the problems of improving traditional and realistic businesses in scheduling production. Wide analyzes show the effectiveness and convergence of the proposed set. The proposed method also shows a very competitive performance when compared to modern engineering methods in literature when tested on general linear programming problems.