Pub. online:4 Jan 2022Type:Research ArticleOpen Access
Journal:Informatica
Volume 33, Issue 3 (2022), pp. 499–522
Abstract
This paper models and solves the scheduling problem of cable manufacturing industries that minimizes the total production cost, including processing, setup, and storing costs. Two hybrid meta-heuristics, which combine simulated annealing and variable neighbourhood search algorithms with tabu search algorithm, are proposed. Applying some case-based theorems and rules, a special initial solution with optimal setup cost is obtained for the algorithms. The computational experiments, including parameter tuning and final experiments over the benchmarks obtained from a real cable manufacturing factory, show superiority of the combination of tabu search and simulated annealing comparing to the other proposed hybrid and classical meta-heuristics.
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 349–360
Abstract
In this paper, we present an effective performance driven placement with global routing algorithm for macro cells. Our algorithm uses a hierarchical, divide and conquer, quad-partitioning approach. The quad-partitioning routine uses the Tabu Search technique. Our algorithm uses the concept of proximity of regions to approximate the interconnection delays during the placement process. In addition, our algorithm can handle modules whose positions are fixed or are restricted to a particular subregion on the layout frame. Our experimental results indicate the superiority of our placement method in terms of quality of solution and run time when compared to Lin and Du (1990).
Journal:Informatica
Volume 4, Issues 1-2 (1993), pp. 172–187
Abstract
It is well known that, in general, exact algorithms for the Quadratic Assignment Problem (QAP) cannot solve problems of size N>15. Therefore, it is necessary to use heuristic approaches for solving large-scale QAPs. In this paper, we consider a class of heuristic approaches based on local search criteria. In particular, we selected four algorithms; CRAFT, Simulated Annealing, TABU search and the Graph Partitioning (GP) approach and studied their relative performance in terms of the quality of solutions and CPU times. All of these algorithms performed roughly the same, based on the results of two sets of test problems executed on an IBM ES/3090-600S computer.