Solving multi-objective supply chain management using non-dominated sorting genetic algorithm

Focusing on production processes is the decisive factor in managing an efficient supply chain that leads to company's success. The objective constraints model include all goals company seeks achieve and level for each. In addition clarifying contribution of each decision variable achieving specified levels different goals, conclusions reached are results prove possibility solving a problem. Applying mathematical according demand parts (derived from final product) contributed significantly saving stock raw materials, as (100) refers quantity kept regular first week varies one another change demand. As result reducing costs associated with it will decrease, difference can be seen total storing materials semi-manufactured parts, which estimated at (47929.1) Iraqi dinars) storage weeks, planning periods established by company. By applying genetic algorithm, were calculated, was (13024.8) dinars, most critical indicator success improving performance.