Local Search Algorithms For Solving A Function With Five-Objectives And Release Dates on One-Machine

Hussein Abdullah Jaafar^1,*,  Hanan Ali Chachan²

¹Department of Mathematics, Open Educational College, Samawah, 66001 , Iraq.

²Department of Mathematics, College of Sciences, University of Mustansiriyah , Baghdad, 10001 , Iraq.

Emails:  alhassen237@gmail.com; Hanan-altaai@yahoo.com

Abstract

In this research, the issue of scheduling n-jobs on one-machine is represented to minimize Five-Objectives-Function (FOF), for finding approximation solutions for the sum of completion time, total tardiness, total earliness, number of late jobs and late work with release date, this issue denoted by:   Hanan and Hussein used a branch and bound technique (B-a-B) to discovery an optimal solution path. Computational results showed the (B-a-B) technique was efficient in solving issues with up to (16- jobs). Because our issue is of a very difficult type (NP-hard), we suggest local search algorithms to discovery near optimal solution.  The execution of local search techniques can be tested on large group of test issues. Computational results showed with up to (30000 jobs) in acceptable time.

Keywords: Branch and Bound (B-a-B); Local Search (LS); Simulated Annealing (SA); Genetic algorithm (GA).