Multi-projects scheduling with resource constraints & Priority rules by the use of Simulated Annealing Algorithm

Ovaj rad predstavlja hibridni genetski algoritam za problem programiranja kod montaže na tekućoj traci s vremenima podešavanja i prijenosa ovisnima o dijelu radne operacije, s ciljevima postizanja smanjenja ponderiranog, zbroja ukupnog ponderiranog kašnjenja na kvadrat, vremenskog intervala, ukupne ponderirane prijevremenosti na kvadrat i broja zakašnjenja. Budući da je problem NP-težak, riješili smo ga hibridnim genetskim algoritmom. Za provjeru predloženog modela korišten je softver Lingo 8.0. Usporedba između rezultata ovog softvera i hibridnog genetskog algoritma pokazuje da kod većih problema (ako je n > 10, gdje je n broj poslova) rezultati dobiveni softverom Lingo 8.0 nisu dovoljno učinkoviti i ne mogu se uspoređivati s predloženim hibridnim genetskim algoritmom u odnosu na vrijeme računanja i devijaciju od minimalne ciljne funkcije. Dani se rezultati ispitivanja za veliki broj rješavanih problema.This paper presents a hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times, with objectives, namely the minimizing of weighted, sum of total weighted squared tardiness, makespan, and total weighted squared earliness and number of tardy jobs. Since the problem is NP-hard, we solved this problem by hybrid genetic algorithm. To validate the proposed model, the Lingo 8.0 software is used. Comparison between the results of the Lingo 8.0 and hybrid genetic algorithm shows that in larger problems (if n > 10, where n is the number of jobs) the results obtained by Lingo do not have good efficiency and cannot be compared with the proposed hybrid genetic algorithm in terms of computational time and deviation from the minimum objective function. Test results are provided for a wide range of problem instances