Single CNC machine scheduling with controllable processing times and multiple due dates

In this study, we solve the single CNC machine scheduling problem with controllable processing times. Our objective is to maximize the total profit that is composed of the revenue generated by the set of scheduled jobs minus the sum of total weighted earliness and weighted tardiness, tooling and machining costs. Customers offer multiple due dates to the manufacturer, each coming with a distinct price for the order that is decreasing as the date gets later, and the manufacturer has the flexibility to accept or reject the orders. We propose a number of ranking rules and scheduling algorithms that we employ in a four-stage heuristic algorithm that determines the processing times for each job and a final schedule for the accepted jobs simultaneously, to maximize the overall profit

Robust airline scheduling with controllable cruise times and chance constraints

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Non-identical parallel CNC machine scheduling

In this study, we solve the non-identical parallel CNC machine scheduling problem. We have two objectives: minimizing the manufacturing cost (comprising machining, non-machining and tooling costs) and minimizing the total weighted tardiness. The tooling constraints affect the non-machining times as well as the machining conditions, such as cutting speed and feed rate, which in turn specify the machining times and tool lives. We propose a two-stage algorithm to find optimal machining conditions and to determine machine allocation, tool allocation and part scheduling decisions. The proposed algorithm generates different schedules according to the relative importance of the objectives

Integrated Scheduling and Tool Management in Flexible Manufacturing Systems

A multistage algorithm is proposed that will solve the scheduling problem in a flexible manufacturing system by..

Joint lot sizing and tool management in a CNC environment

We propose a new algorithm to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously to minimize total production cost in a CNC environment. Most of the existing lot sizing and tool management methods solve these problems independently using a two-level optimization approach. Thus, we not only improve the overall solution by exploiting the interactions among these decision making problems, but also prevent any infeasibility that might occur for the tool management problem due to decisions made at the lot sizing level. The computational experiments showed that in a set of randomly generated problems 22.5 % of solutions found by the two-level approach were infeasible and the proposed joint approach improved the solution on the average by 6.79 % for the remainin