An Advanced Optimization Technique for Smart Production Using α -Cut Based Quadrilateral Fuzzy Number

In the design phase of a new smart product, production costs are unpredictable due to location, transport, and engineering design. In these situations, consequently, cost optimization becomes ambiguous. This paper presents a methodology to obtain optimization through a fuzzy linear programming problem (FLPP) in which fuzzy numbers signify the right-side parameters. The comparative investigation of modeling and optimizing creation cost through a new α-cut based quadrilateral fuzzy number is proposed to solve the fuzzy linear programming and the necessary operations on the proposed number. Due to the probabilistic increase and decrease in the accessibility of the various constraints, the actual expected total cost fluctuates. In this respect, a unique situation of instability is incorporated, and reasonable models to reduce the cost of eradication in the creation process are presented. The main endeavor is made to look at the credibility of optimized cost utilizing the α-cut based quadrilateral FLPP models, and the outcome is contrasted with its augmentation. The data of the production cost of RCF Kapurthala is taken, and the creation expenses of various mentors from the year 2010–2011 are considered as input parameters. The aggregate cost is focused on the objective function. The least low, lower, upper, and most upper bounds are computed for each situation, and then systems of optimized fuzzy LPP are constructed. The credibility of quadrilateral fuzzy LPP concerning all situations is obtained and using this membership grade, the minimum, and highest minimum costs are illustrated.