Chou-Jung Hsu

Unrelated parallel-machine scheduling with aging effects and multi-maintenance activities

Machine maintenance is often performed in manufacturing to prevent premature machine failures with a view to sustaining production efficiency. In this paper we study the parallel-machine scheduling problem with aging effects and multi-maintenance activities simultaneously. We assume that each machine may be subject to several maintenance activities over the scheduling horizon. A machine reverts to its initial condition after maintenance and the aging effects start anew. The objective is to find jointly the optimal maintenance frequencies, the optimal positions of the maintenance activities, and the optimal job sequences such that the total machine load is minimized. We apply the group balance principle to obtain the optimal positions of the maintenance activities and the number of jobs in each group in the scheduling sequence on each machine. We provide an efficient algorithm to solve the problem when the maintenance frequencies on the machines are given.

Unrelated parallel-machine scheduling with rate-modifying activities to minimize the total completion time

Zhao et al. (2009) [24] study the m identical parallel-machine scheduling problem with rate-modifying activities to minimize the total completion time. They show that the problem can be solved in O(n^2^m^+^3) time. In this study we extend the scheduling environment to the unrelated parallel-machine setting and present a more efficient algorithm to solve the extended problem. For the cases where the rate-modifying rate is (i) larger than 0 and not larger than 1, and (ii) larger than 0, we show that the problem can be solved in O(n^m^+^3) and O(n^2^m^+^2) time, respectively.

MINIMIZING THE MAKESPAN IN A SINGLE MACHINE SCHEDULING PROBLEM WITH A FLEXIBLE MAINTENANCE

ABSTRACT This paper considers a single machine scheduling problem with a flexible maintenance, we consider the machine should be stopped to maintain or to reset for a constant time r during the scheduling period. Meanwhile we assume that the maintenance period [s, t] is arranged previously; and the time r would not be longer than the maintenance period [s, t] (i.e. r ≤ t-s). The time s (t) is the earliest (latest) time at which the machine starts (stops) its maintenance. The objective is to minimize the makespan (maximum completion time). This scheduling problem is often occurred in computer center, NC-machine and IC-testing machine for the jobs scheduling and repairmen arrangement. In this paper, the proposed problem is shown to be NP-hard. A heuristic algorithm with computational experiments is provided. An extension with more than one maintenance intervals is also considered.

A two-machine flowshop scheduling problem with a separated maintenance constraint

This paper considers a two-machine flowshop scheduling problem with a separated maintenance constraint. This means that the machine may not always be available during the scheduling period. It needs a constant time to maintain the machine after completing a fixed number of jobs at most. The objective is to find the optimal job combinations and the optimal job schedule such that the makespan is minimized. The proposed problem has some practical applications, for example, in electroplating process, the electrolytic cell needs to be cleaned and made up a deficiency of medicine. In this paper, we propose a heuristic algorithm to solve this problem. Some polynomially solvable cases and computational experiments are also provided.

Unrelated parallel-machine scheduling problems with aging effects and deteriorating maintenance activities

This paper explores the problems of unrelated parallel-machine scheduling with aging effects and deteriorating maintenance activities. The jobs are non-resumable. Each machine has at most one maintenance activity which is allowed throughout the planning horizon. Assume that once the maintenance activity is completed, the functions of machine and the properties of jobs e.g. the temperature (hardness) of materials that processed by the machine will be restored to their initial conditions. The length of the maintenance activity is a linear function of its starting time. The objectives of this study are to minimize the total completion time and the total machine load. Three basic types of aging effect model are proposed. We show that all the proposed models can be solved optimally in polynomial time.

Worst-case and numerical analysis of heuristic algorithms for flowshop scheduling problems with a time-dependent learning effect

In this paper, we investigate a time-dependent learning effect in a flowshop scheduling problem. We assume that the time-dependent learning effect of a job was a function of the total normal processing time of jobs scheduled before the job. The following objective functions are explored: the makespan, the total flowtime, the sum of weighted completion times, the sum of the kth power of completion times, and the maximum lateness. Some heuristic algorithms with worst-case analysis for the objective functions are given. Moreover, a polynomial algorithm is proposed for the special case with identical processing time on each machine and that with an increasing series of dominating machines, respectively. Finally, the computational results to evaluate the performance of the heuristics are provided.

A branch-and-bound procedure for a single-machine earliness scheduling problem with two agents

This paper addresses a two-agent scheduling problem on a single machine where the objective is to minimize the total weighted earliness cost of all jobs, while keeping the earliness cost of one agent below or at a fixed level Q. A mixed-integer programming (MIP) model is first formulated to find the optimal solution which is useful for small-size problem instances. To solve medium- to large-size problem instances, a branch-and-bound algorithm incorporating with several dominance properties and a lower bound is then provided to derive the optimal solution. A simulated annealing heuristic algorithm incorporating with a heuristic procedure is developed to derive the near-optimal solutions for the problem. A computational experiment is also conducted to evaluate the performance of the proposed algorithms.

Some unrelated parallel machine scheduling problems with past-sequence-dependent setup time and learning effects

In this paper, we study an unrelated parallel machine scheduling problem simultaneously with learning effect and setup time. The setup time is proportional to the length of the already processed jobs. That is, the setup time of each job is past-sequence-dependent. The objective is to minimize the total absolute deviation of job completion times. We show that the proposed problem is polynomially solvable.

Two due date assignment problems with position-dependent processing time on a single-machine

The focus of this study is to analyze single-machine scheduling and due date assignment problems with position-dependent processing time. Two generally positional deterioration models and two frequent due date assignment methods are investigated. The objective functions include the cost of changing the due dates, the total cost of positional weight earliness, and the total cost of the discarded jobs that cannot be completed by their due dates. We conclude that the problems are polynomial time solvable. Significantly enough, after assessing the special case of each problem, this research found out that they can be optimally solved by lower order algorithms.

Single-machine scheduling with deteriorating jobs and aging effects under an optional maintenance activity consideration

This article studies a single-machine scheduling with deteriorating jobs and aging effects under an optional maintenance activity. We assume that after maintenance activity, the machine will revert to its initial condition and the aging effects will start anew. Moreover, due to the restriction of budget of maintenance, the limitation of the maintenance frequency on the machine is assumed to be known in advance. The optional maintenance activity of this study means that the starting time of the maintenance activity is unknown in advance. It can be scheduled immediately after the processing of any job that has been completed. Therefore, the planner must to make decision on whether or when to schedule the maintenance activity during the scheduling horizon to optimal the performance measures. The objective is to minimize the makespan. We first show that the addressed problem is NP-hard in the strong sense. Then a fully polynomial-time approximation scheme (FPTAS) for the proposed problem is presented.