Parallel machine total tardiness scheduling with a new hybrid metaheuristic approach
Computers and Operations Research
EcoSimNet: A Multi-Agent System for Ecological Simulation and Optimization
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Intelligent farmer agent for multi-agent ecological simulations optimization
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Solving the integrated product mix-outsourcing problem using the Imperialist Competitive Algorithm
Expert Systems with Applications: An International Journal
A genetic algorithm-based scheduler for multiproduct parallel machine sheet metal job shop
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In the recent years, theory of constraints (TOC) has emerged as an effective management philosophy for solving decision making problems with the aim of profit maximization by considering the bottleneck in traditional as well as modern manufacturing plants. One of the key components of TOC application is to enumerate quantity of the various products to be manufactured keeping in view the system constraints. Problem of this kind is termed as TOC product mix decision problem. It is a well-known computationally complex problem and thus warrants the application of heuristics techniques or AI based optimization tools to achieve optimal or near optimal solution in real time. In this research, a hybrid algorithm named tabu-simulated annealing is proposed. It exploits the beauty of tabu search and simulated annealing (SA) to ensure the convergence at faster rate. It is found that the performance of hybrid tabu-SA algorithm on a well known data set of product mix optimization problem is superior as compared to tabu search, SA, TOC heuristic, Revised-TOC (R-TOC) heuristic, and Integer Linear Programming (ILP) based approaches.