Parallel machines scheduling with machine preference via agent-based approach

Abstract

This paper deals with parallel machines scheduling for electro-etching in the manufacturing processes of aluminum foil. Due to the attributes of the machines and the fitness of jobs to each, the processing time and setup time for a job depends on the machine on which the job is processed. In this paper, the application of agent-based multi-negotiation mechanism is developed for this manufacturing environment and for further scheduling uncertainty research. To support the dynamic negotiation mechanism between jobs and machines, three categories of agents are currently employed by the system. They are job agents, machine agents and supervisor agent. To establish job allocations, job agents and machine agents have to bid interactively in accordance with the decision model embedded in. Supervisor agent is designed to manage negotiation process between job agents and machine agents to ensure the global bi-objective of system are being observed. Experiments were conducted to evaluate the performance of the proposed architecture. Computational experiences demonstrate that the proposed architecture can work more efficiently and is capable of obtaining better solutions to the heuristic based on earliest-due-date rule applied by enterprise practice on case company.