Stochastic Solid Transportation Problem Multi- Objective Multi-Item by using Gamma Distribution

In this research paper, the complex problem of Multi-objective Multi-item Stochastic Solid Transportation Problem (MOMSSTP) with random parameters as stochastic nature.Traditional transportation models often fail to capture the intricacies of modern logistical operations, where multiple conflicting objectives, diverse item types and uncertain conditions are prevalent.Our study formulates an advanced MOMSSTP framework that incorporates these factors, aiming to optimize cost of transportation and time of transportation.Stochastic elements are introduced to account for uncertainties in origin's supply, conveyance's capacity and destination's demand which making the model robust and adaptable to variable operational conditions.On the basis of chance constraint programming suggest an approach to tackle the multi-objective multi-item stochastic solid transportation problem with random parameters characterized through gamma distribution and also used fuzzy programming approach for optimization.The effectiveness of our approach is demonstrating through a numerical example.