Optimization algorithms for transportation problems with stochastic demand

Abstract

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to minimize the total costs, Where the approved model was able to minimize the total costs by 25%. A future study investigating optimization heuristic with stochastics demand would be very interesting.

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

“…The multi-objectives model was built, where the objective constraints in the model include all the goals the company seeks to achieve and the level to achieve for each of them, in addition to clarifying the contribution of each decision variable in achieving the specified levels of the different goals [18,19].…”