A Hybrid Approach for Efficiently Solving Multi-Criteria Scheduling Problems on a Single Machine
Year: 2024
Type: article
Abstract: The presented study investigates the scheduling regarding jobs on a single machine. Each job is processed with no interruptions and becomes available for processing at time 0. The aim is to find a processing order with regard to jobs, minimizing “multi-criteria and multi-objective” for two problems. The first problem considers the summation completion time , summation late work , and maximal tardiness , while the second problem considers the total completion time , total earliness , and maximum tardiness . In addition, a sub-problem is presented for each problem and denoted by 1// and 1// for the first and second problems, respectively, which is an NP-hard problem. Two meta-heuristics methods “particle swarm optimization (PSO) and bee algorithm (BA)” were applied to acquire the optimal or near-optimal solution. Meta-heuristics methods solve problems of up to jobs. Finally, in an attempt to increase the overall search efficiency, a hybrid algorithm was created by combining two algorithms, a hybrid between and was created to create an alternative search method that incorporates the best properties that each method offers during problem-solving. Moreover, by comparing the performance of local search methods with a hybrid strategy, the hybrid strategy method outperforms BA and PSO. In addition, it can solve problems up to jobs. Arithmetic results are calculated by coding (programming) algorithms using (MATLAB 2019a).
Source: Iraqi Journal of Science
Authors: Nagham Muosa Neamah, Bayda Atiya Kalaf
Institution: University of Baghdad
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405952315