Optimisation of distribution networks using Genetic Algorithms. Part 1 – problem modelling and automatic generation of solutions

This paper presents a generalised methodology developed for the optimisation of the distribution networks based on Genetic Algorithms (GA). Specifically, it focuses on capacitated Location–Allocation problems. The approach is general, permitting, at this stage, the use of any combination of transportation and warehousing costs for a deterministic demand. Moreover, the methodology has been designed to have the flexibility to be adapted, in the future, for other realistic conditions and constraints: stochastic conditions, multi-echelon Supply Chain, direct and reverse logistics, single or multi-commodities, seasonal production, etc. Due to the complexity and extent of the problem, the paper was split into two parts. The first part deals with modelling of the problem and the automatic generation of the initial population of chromosomes – a set of solutions to the problem. The second part of the paper details the full GA and the genetic operators. An example of applying the algorithm for 25 Production Facilities (PFs), 10 warehouses and 25 retailers (520 variables interrelated with complex constraints) is presented, demonstrating the robustness of the algorithm and its capacity to tackle problems of practical size.