This paper presents the salient aspects of a simulation-based experimental study of scheduling rules for scheduling a dynamic job shop in which the setup times are sequence dependent. A discrete event simulation model of the job shop system is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model. Five new setup-oriente...

Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization criterion is satisfied. According to the restr...

A hybrid flow shop (HFS) is a generalized flow shop with multiple machines in some stages. HFS is fairly common in flexible manufacturing and in process industry. Because manufacturing systems often operate in a stochastic and dynamic environment, dynamic hybrid flow shop scheduling is frequently encountered in practice. This paper proposes a neural network model and algorithm to solve the dyna...

We discuss the application of economic coordination mechanisms to scheduling problems in manufacturing and logistics. We use job shop scheduling as a sample problem domain. We study economically augmented job shop problems (EJSP) which comprise valuation information. We demonstrate how instances of EJSP can be mapped to combinatorial job shop auction problems (CJSAP). A discussion of the tracta...

This paper explores the relationship between the three beliefs about online shopping ie. perceived usefulness, perceived ease of use and perceived enjoyment and intention to shop online. A sample of 150 respondents was selected using a purposive sampling method whereby the respondents have to be Internet users to be included in the survey. A structured, self-administered questionnaire was used ...

Multi-objective open-shop scheduling is definitely significant in practical. However, the research focused on multi-objective open-shop scheduling was relatively scarce. This article proposed a particle swarm optimization to address open-shop scheduling problems with multiple objectives. Originally, particle swarm optimization was invented to treat continuous optimization problems. In this pape...

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. In this paper, a novel job shop approach is proposed to create a more efficient integrated harvesting and sugarcane transport scheduling system to reduce the cost of sugarcane transport. There are several benefits that can be attained by treating the train scheduling problem as a job shop pro...

In this paper a new neuro-genetic architecture is presented that solves a profit oriented dynamic job shop problem. In the job shop order acceptance and scheduling problem new jobs arrive continuously and because of insufficient job shop capacity, a selection has to be made among the offered jobs. The goal is to find an order acceptance policy, which is supported by a scheduling policy, that ma...

This article presents a deterministic model for rough-cut cost estimation in a capacitated madeto-order environment. We assume that a firm can execute each job either at its own shop or by outsourcing it. The model calculates the unit cost of each product while taking into account the shop floor rough-cut capacity planning, and by determining what to produce in the firm’s shop and what to outso...

A learning stage of scheduling tends to produce knowledge about a benchmark of priority dispatching rules which allows a scheduler to improve the solution quality for a set of similar job-shop problems. Once trained on the sample job-shop problems (usually with small sizes), the adaptive algorithm solves a similar job-shop problem (with a moderate size or a large size) better than heuristics us...