Mathematical Model on Multi Objective Subtask Scheduling Problems using Heuristic Algorithm

Abstract

Scheduling in general defined as the process of assigning number of tasks to newlinethe available limited resources with the goal of meeting the endorsed objectives. newlineScheduling in manufacturing industries is defined as the process of allocating n newlinejobs to the available m machines to achieve the time based objectives such as newlineminimizing the makespan, tardiness, lateness , due date etc. and the cost based newlineobjectives such as production cost, transportation cost etc. As the manufacturing newlineindustries play a vital role in contributing to the economy of a nation, the newlinedevelopment of an efficient scheduling system to increase the growth rate and newlineproductivity becomes the prior requirement. This research is dedicated to develop an newlineefficient scheduling system and a mathematical model for multi-objective subtask newlinescheduling problems in manufacturing industries. The multi-objectives considered in newlinethis research includes minimizing the load balance and cost for industrial robots, newlineminimizing the total weighted completion time for customer order scheduling, newlineestablished a good mathematical model for customer order scheduling problem to newlineinvestigate the problem size for the optimality with the objective of minimizing the newlinemakespan, adopted mixed integer linear programming model with mixed composition newlinestructure for Service Selection and Optimization Scheduling Problem (SSOSP), the newlinemain objectives are cost, time and quality with incorporation of transportation time newlineand transportation cost along with manufacturing cost and time. In order to achieve newlinethe aforementioned objectives, this research adopted heuristic based algorithms such newlineas Artificial Immune System (AIS), Particle Swam Optimization (PSO), Subtask newlineScheduling Algorithm (SSA) and Fuzzy based min-max rule algorithm. newline