Optimization of Job Shop Scheduling Problem using Tabu Search Optimization Technique

ABSTRACT-The Job shop scheduling (JSS) problem consists of "n" jobs and "m" operations on each of the jobs and it is hardest combinatorial optimization problems for which it is extremely difficult to find optimal solutions. Past two decades, much attention has been made to general heuristics such as Genetic algorithm, Ant Colony Optimization, Tabu Search and Simulated Annealing to solve this type of combinatorial optimization problems. In this paper we present how the adaptive search algorithms namely Tabu search is applied to solve Job shop scheduling (JSS) problem. The method uses dispatching rules to obtain an initial solution and searches for new solutions in a neighborhood based on the critical paths of the jobs. Several benchmark problems are tested using this algorithm for the best makespan and the obtained results are encouraging when compared with benchmark values

Design of a solution technique based on an integral approach for the Flexible Open-Flow Shop scheduling problem

In manufacturing industries, scheduling is a form of decision-making that plays a crucial role. The determination of the methods by which a set of jobs must be manufactured in order to seek specific goals leads to the development of different schedule techniques. However, scheduling depends on the type of workshop or manufacturing environment such as open shop, job shop and flow shop. There are cases that more than one environment for the same manufacturing process could coexist. This project deals with a specific scheduling problem in which each job is processed under the combination of two shop environments; the first one is related to an open shop while the second one corresponds to a flow shop; this problem is called the Flexible open-flow shop (FOFS). These types of scheduling problems present NP-hardness, meaning the neediness of sophisticated algorithms to find solutions in reasonable computational times. Additionally, are commonly solved separately or by approximating into another workshop, leaving the interaction of both environments irrelevant. Thus, the main objective of this project is to design solution techniques based on an integral approach to minimize the maximum completion time also known as makespan.Ingeniero (a) IndustrialPregrad

A fast tabu search algorithm for the group shop scheduling problem

Three types of shop scheduling problems, the flow shop, the job shop and the open shop scheduling problems, have been widely studied in the literature. However, very few articles address the group shop scheduling problem introduced in 1997, which is a general formulation that covers the three above mentioned shop scheduling problems and the mixed shop scheduling problem. In this paper, we apply tabu search to the group shop scheduling problem and evaluate the performance of the algorithm on a set of benchmark problems. The computational results show that our tabu search algorithm is typically more efficient and faster than the other methods proposed in the literature. Furthermore, the proposed tabu search method has found some new best solutions of the benchmark instances