A new mathematical model for single machine batch scheduling problem for minimizing maximum lateness with deteriorating jobs

This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model

A new lower bound approach for single-machine multicriteria scheduling

The concept of maximum potential improvement has played an important role in computing lower bounds for single-machine scheduling problems with composite objective functions that are linear in the job completion times. We introduce a new method for lower bound computation; objective splitting. We show that it dominates the maximum potential improvement method in terms of speed and quality

Parallel machine scheduling with release dates, due dates and family setup times

In manufacturing, there is a fundamental conflict between efficient production and delivery performance. Maximizing machine utilization by batching similar jobs may lead to poor delivery performance. Minimizing customers' dissatisfaction may lead to an inefficient use of the machines. In this paper, we consider the problem of scheduling n independent jobs with release dates, due dates, and family setup times on m parallel machines. The objective is to minimize the maximum lateness of any job. We present a branch-and-bound algorithm to solve this problem. This algorithm exploits the fact that an optimal schedule is contained in a specific subset of all feasible schedules. For lower bounding purposes, we see setup times as setup jobs with release dates, due dates and processing times. We present two lower bounds for the problem with setup jobs, one of which proceeds by allowing preemption

Existence Theorems for Scheduling to Meet Two Objectives

We will look at the existence of schedules which are simultaneously near-optimal for two criteria. First,we will present some techniques for proving existence theorems,in a very general setting,for bicriterion scheduling problems. We will then use these techniques to prove existence theorems for a large class of problems. We will consider the relationship between objective functions based on completion time,flow time,lateness and the number of on-time jobs. We will also present negative results first for the problem of simultaneously minimizing the maximum flow time and average weighted flow time and second for minimizing the maximum flow time and simultaneously maximizing the number of on-time jobs. In some cases we will also present lower bounds and algorithms that approach our bicriterion existence theorems. Finally we will improve upon our general existence results in one more specific environment

The Integration of Process Planning and Shop Floor Scheduling in Small Batch Part Manufacturing

In this paper we explore possibilities to cut manufacturing leadtimes and to improve delivery performance in a small batch part manufacturing shop by integrating process planning and shop floor scheduling. Using a set of initial process plans (one for each order in the shop), we exploit a resource decomposition procedure to determine schedules to determine schedules which minimize the maximum lateness, given these process plans. If the resulting schedule is still unsatisfactory, a critical path analysis is performed to select jobs as candidates for alternative process plans. In this way, an excellent due date performance can be achieved, with a minimum of process planning and scheduling effort

About one algorithm for solving scheduling problem

© 2015, Pleiades Publishing, Ltd. In this paper we proved the new properties optimal schedules for unknown strongly NP-complete scheduling problem of minimizing maximum lateness on a single machine, not allowing preemption. Pseudopolynomial implementation of the general scheme for solving that problem based on these properties is developed