Simulation Modelling and Analysis of Due Date Assignment Methods and Scheduling Decision Rules in a Flexible Manufacturing System

This paper presents the salient details of a simulation-based study conducted to analyze the effect of due date assignment methods and scheduling decision rules on the performance of a flexible manufacturing system. A typical FMS is considered for investigation in the present study. Three endogenous due date setting methods and one exogenous method are examined in the present study. The scheduling rules considered for experimentation include processing time based rules and due date based rules in addition to the unbiased first-in-first-out rule. The performance measures evaluated in the present study are mean flow time, standard deviation of flow time, mean tardiness, standard deviation of tardiness, percentage of tardy jobs and average flow allowance. Analysis of the simulation results reveal that the dynamic due date setting methods provide better system performance.

The Parallel Machine Scheduling with Considering the Due Date Assignment, Earliness, Weighted Number of Tardy Jobs and Batch Delivery

In this paper, parallel machine scheduling problem is considered under due date assignment, earliness, weighted number of tardy jobs, facilities costs and shipping products by limited vehicle capacity. The orders of the customer are presented with a due date. Each order is scheduled and assigned to one of the machines according to due date, delay weight and penalty of increasing of due date and shipped in the batch. The problem is known as NP-hardness, therefore a Genetic Algorithm (GA) is proposed to solve the problem. The results are also compared with the CPLEX solver in the GAMS. Finally, sensitivity analysis for the problem parameters is performed in relation to the objective function. The results showed a direct relationship between objective function with the weighted tardiness and processing time, also an inverse relationship with the number of machines and vehicle capacity.

Optimization for Due-Date Assignment Single-Machine Scheduling under Group Technology

In this paper, the single-machine scheduling problem is studied by simultaneously considering due-date assignment and group technology (GT). The objective is to determine the optimal sequence of groups and jobs within groups and optimal due-date assignment to minimize the weighted sum of the absolute value in lateness and due-date assignment cost, where the weights are position dependent. For the common (CON) due-date assignment, slack (SLK) due-date assignment, and different (DIF) due-date assignment, an O n log n time algorithm is proposed, respectively, to solve the problem, where n is the number of jobs.

Solution Algorithms for Single-Machine Group Scheduling with Learning Effect and Convex Resource Allocation

This paper deals with a single-machine resource allocation scheduling problem with learning effect and group technology. Under slack due-date assignment, our objective is to determine the optimal sequence of jobs and groups, optimal due-date assignment, and optimal resource allocation such that the weighted sum of earliness and tardiness penalties, common flow allowances, and resource consumption cost is minimized. For three special cases, it is proved that the problem can be solved in polynomial time. To solve the general case of problem, the heuristic, tabu search, and branch-and-bound algorithms are proposed.