The present article proposes an exact algorithm for the single-machine scheduling problem to minimize the sum of total completion times, range of lateness and maximum tardiness on a single machine (1/ /(∑ C_(σ_j + R_L + T_max)), where machine idle time is prohibited. In this paper, one of the multiobjective function problem for single criteria on just one machine is being studied. To obtain the optimal solution for the suggested problem, we propose to use Branch and Bound method (BAB) depending upon some dominance rules. This exact method used new technique to obtain three upper bounds (UB) and single lower bound (LB). The proposed BAB method proved its sufficiency by the practical results for n ≤ 15 in a reasonable time. Lastly, we proved a theorem as special case for our problem.
In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for jobs in a reasonable time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.