𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A simulated annealing approach to minimize the maximum lateness on uniform parallel machines

✍ Scribed by Kai Li; Shan-Lin Yang; Hua-Wei Ma


Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
314 KB
Volume
53
Category
Article
ISSN
0895-7177

No coin nor oath required. For personal study only.

✦ Synopsis


This paper considers the uniform parallel machine scheduling problem which is to minimize the maximum lateness. This problem is equivalent to the uniform parallel machine scheduling problem, which is to minimize the maximal completion time of n jobs whose release times are zero, processing times depend on the speed of the machine to which they are assigned, and their delivery times are different. This problem is NP-hard, even if the machines' speeds are identical and all the delivery times equal to zero. We propose a simulated annealing algorithm, named LPDT-SA, to obtain solutions with high quality for large-sized problems. A heuristic algorithm LPDT is built to generate initial solutions. An effective method for solution representation is designed, which is efficient to realize the swap and insertion neighborhood, and simultaneously avoid some obvious inferior solutions, therefore the efficiency of the proposed simulated annealing algorithm is improved. A large set of instances are generated randomly to test the solution quality of LPDT-SA and assess its runtime. The results and analysis of experiments are reported and discussed.


πŸ“œ SIMILAR VOLUMES


Scheduling identical jobs with unequal r
✍ Maged M. Dessouky πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 308 KB

AbstractÐWe consider the problem of scheduling n identical jobs with unequal ready times on m parallel uniform machines to minimize the maximum lateness. This paper develops a branch-and-bound procedure that optimally solves the problem and introduces six simple single-pass heuristic procedures that

A Methodological Approach to Parallel Si
✍ Alessandro Bevilacqua πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 217 KB

Simulated annealing (SA) is a stochastic optimization technique which guarantees under certain conditions to converge to a global minimum. The major disadvantage of this technique is its very slow convergence: this makes it not suitable for many complex optimization problems. Different parallel vers