A multi-objective car sequencing problem on two-sided assembly lines

The car sequencing problem consists of sequencing a given set of cars to be produced in each day. this paper presents an application of the extended coincident algorithm (coin-e), which is an instance of the estimation of distribution algorithms, to a multi-objective car sequencing problem on a more realistic platform, i.e. two-sided assembly lines. three conflicting objectives are optimised simultaneously in a pareto sense including minimise the number of paint colour changes, minimise the total number of ratio constraint violations and minimise the utility work. the performances of coin-e are compared with coin (its original version), nsga ii, dpso and bbo. the results reveal that coin-e is superior to the other contestant algorithms in both solution quality and diversity.