Providing an integrated multi-depot vehicle routing problem model with simultaneous pickup and delivery and package layout under uncertainty with fuzzy-robust box optimization method

This paper modeled and solved an integrated multi-depot vehicle routing problem (MDVRP) with simultaneous pickup delivery (SPD) package layout under unpredictable pickup, delivery, transfer costs. The model described in this is divided into two stages. In the first stage, SCA algorithm used to optimize dimensions (a collection of commodities consumers need). NSGA II MOALO algorithms are second stage three objective functions 1 simultaneously) minimizing total costs, 2) co2 emissions, 3) maximum working hours drivers based on optimal (length, width, height) obtained from solving model. Determining quantity ideal location possible warehouses, best route for trucks take deliver collect customer items, distribution customers warehouses key goals stage. Since unclear, problem's uncertainty parameters controlled using a novel fuzzy-robust box optimization (FRBO) technique. technique, which combines advantages fuzzy programming robust box-based optimization, produces excellent results when functions. numerical calculations example show that network costs CO2 emissions increased presented increasing rate. At same time, decreased due shortened communication number vehicles increasing. Finally, was resolve case study at Safir Broadcasting Company because its efficiency resolving created model, findings revealed presence 13 potential effective solutions. greenhouse gas rose by 1.11%, overall expenditures climbed 1.72%, worked fell 11.98% rate raised 0.5 0.7, according research FRBO.