Journal ArticleDOI
Order Acceptance and Scheduling Decisions in Make-to-Order Systems
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TLDR
Three heuristic algorithms are developed to solve large sized problems and Computational tests indicate that the proposed algorithms are both computationally efficient and effective even for instances up to 300 orders.About:
This article is published in International Journal of Production Economics.The article was published on 2010-05-01. It has received 154 citations till now. The article focuses on the topics: Single-machine scheduling & Build to order.read more
Citations
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Journal ArticleDOI
Order acceptance and scheduling: A taxonomy and review
TL;DR: A taxonomy and a review of this literature is presented, its contributions are cataloged, and opportunities for future research in this area are suggested.
Journal ArticleDOI
A survey on offline scheduling with rejection
TL;DR: The purpose of this survey is to offer a unified framework for offline scheduling with rejection by presenting an up-to-date survey of the results in this field, and highlights the close connection between scheduling with reject and other fields of research such as scheduling with controllable processing times and scheduling with due date assignment.
Journal ArticleDOI
Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system
V. Vinod,R. Sridharan +1 more
TL;DR: The salient aspects of a simulation study conducted to investigate the interaction between due-date assignment methods and scheduling rules in a typical dynamic job shop production system are presented and it is found that dynamic due- date assignment methods provide better performance.
Journal ArticleDOI
A tabu search algorithm for order acceptance and scheduling
TL;DR: A tabu search algorithm is presented that solves the order acceptance and scheduling problem on a single machine with release dates and sequence dependent setup times and gives near optimal solutions that are significantly better compared to the solutions given by the two heuristics.
Journal ArticleDOI
Single machine scheduling with release dates and rejection
TL;DR: This paper considers the single machine scheduling problem with release dates and rejection, shows that the problem is NP-hard in the ordinary sense, and provides two pseudo-polynomial-time algorithms that can be solved in polynomial-time.
References
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Journal ArticleDOI
Integer Programming Formulation of Traveling Salesman Problems
TL;DR: The present paper provides yet another example of the versatility of integer programming as a mathematical modeling device by representing a generalization of the well-known “Travelling Salesman Problem” in integer programming terms.
Book ChapterDOI
Solution of a Large-Scale Traveling-Salesman Problem
TL;DR: The RAND Corporation in the early 1950s contained Arrow, Bellman, Dantzig, Flood, Ford, Fulkerson, Gale, Johnson, Nash, Orchard-Hays, Robinson, Shapley, Simon, Wagner, and other household names as discussed by the authors.
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A survey of scheduling problems with setup times or costs
TL;DR: An extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers is provided, which classifies scheduling problems into those with batching and non-batching considerations, and with sequence-independent and sequence-dependent setup times.
Journal ArticleDOI
A review of scheduling research involving setup considerations
TL;DR: A comprehensive review of the literature on scheduling problems involving setup times (costs) classifies scheduling problems into batch and non-batch, sequence-independent and sequence-dependent setup, and categorizes the literature according to the shop environments of single machine, parallel machines, flowshops, and job shops.
Journal ArticleDOI
Scheduling with Deadlines and Loss Functions
TL;DR: The problem of this paper is that of scheduling several one-stage tasks on several processors, which are capable of handling the tasks with varying degrees of efficiency, to minimize the total loss, which is a sum of losses associated with the individual tasks.