job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...

This paper proposes a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA ...

Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by propos...

We discuss the application of economic coordination mechanisms to scheduling problems in manufacturing and logistics. We use job shop scheduling as a sample problem domain. We study economically augmented job shop problems (EJSP) which comprise valuation information. We demonstrate how instances of EJSP can be mapped to combinatorial job shop auction problems (CJSAP). A discussion of the tracta...

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. In this paper, a novel job shop approach is proposed to create a more efficient integrated harvesting and sugarcane transport scheduling system to reduce the cost of sugarcane transport. There are several benefits that can be attained by treating the train scheduling problem as a job shop pro...

In this paper a new neuro-genetic architecture is presented that solves a profit oriented dynamic job shop problem. In the job shop order acceptance and scheduling problem new jobs arrive continuously and because of insufficient job shop capacity, a selection has to be made among the offered jobs. The goal is to find an order acceptance policy, which is supported by a scheduling policy, that ma...

A learning stage of scheduling tends to produce knowledge about a benchmark of priority dispatching rules which allows a scheduler to improve the solution quality for a set of similar job-shop problems. Once trained on the sample job-shop problems (usually with small sizes), the adaptive algorithm solves a similar job-shop problem (with a moderate size or a large size) better than heuristics us...

The paper presents an enterprise application that integrates material requirement planning (MRP) with job shop simulator using distributed object technology. The application aims to realize an integrated system that has rapid response to changing requirements and capability to integrate heterogeneous manufacturing facilities. At first, the application accepts the customer’s order and performs m...

We use the Akers-Friedman geometric approach to solve the two jobs job-shop problem when there is an earliness cost on the first operation and a tardiness cost on the last operation of each job. We then generalize the problem by imposing earliness and tardiness costs on each operation and finally, we solve it using a dynamic programming algorithm. KeywordsEarliness-tardiness scheduling, Polyn...

General job-shop scheduling is a difficult problem to be solved. The complexity of the problem is highlighted by the fact that in a general job-shop having m machines and n jobs the total number of schedules can be as high as (n!), hence if “n=20 m=10” the number of possible solutions is 7.2651x10. Many approaches such as Branch and Bound, Simulated Annealing, Tabu Search and others have been t...