9373274
A heuristic for parallel machine scheduling with agreeable due dates to minimize the number of late jobs
Abstract Given a set of identical parallel machines and a set of jobs with different due dates and release times, we consider the problem of finding a schedule such that the number of late jobs is minimized, where the given due dates and release times are assumed to be agreeable. A heuristic algorithm is presented and a dynamic programming lower bounding procedure is developed. Computational experiments are performed to show the effectiveness of the heuristic.
4532231
On the Fixed Interval Due-date Scheduling Problem
Abstract We consider the nonpreemptive single machine scheduling problem with multiple due-dates (delivery dates), where the time between two consecutive due-dates is a constant. Given a set of jobs, we are interested in scheduling the jobs such that the sum of the total due-date cost and the total earliness cost is minimized with the constraint that each job must be finished at or before its due-date. We show that this problem is strongly NP-hard in general. We then analyze the problem where the number of due-dates is bounded by a given constant. We describe a pseudo-polynomial dynamic programming algorithm for this restricted problem. A heuristic is also provided and worst-case analysis is performed. An efficient algorithm is developed to solve the special case where all the job processing times are identical.
37859404
Single-machine scheduling to minimize the weighted number of early and tardy agreeable jobs
Abstract We consider a single-machine scheduling problem in which every job has a given target start time and a due-date. A job is early if processing commences before its start time and is tardy if it is completed after its due-date. The objective is to minimize the weighted number of early and tardy jobs, with the restriction that the start times and due-dates are “agreeable”, i.e., the start times must increase in the same sequence as the due-dates. We show that the problem is NP-complete in the strong sense. The complexity issues and algorithms for some special cases of this problem are discussed, and heuristic algorithms are developed for the general problem. Computational experiments are conducted to show the effectiveness of the heuristics.
17199559
Data Mining for Direct Marketing: Problems and Solutions
Direct marketing is a process of identifying likely buyers of certain products and promoting the products accordingly. It is increasingly used by banks, insurance companies, and the retail industry. Data mining can provide an effective tool for direct marketing. During data mining, several specific problems arise. For example, the class distribution is extremely unbalanced (the response rate is about 1%), the predictive accuracy is no longer suitable for evaluating learning methods, and the number of examples can be too large. In this paper, we discuss methods of coping with these problems based on our experience on direct-marketing projects using data mining.
8510271
Supporting Efficient Record Linkage for Large Data Sets Using Mapping Techniques
This paper describes an efficient approach to record linkage. Given two lists of records, the record-linkage problem consists of determining all pairs that are similar to each other, where the overall similarity between two records is defined based on domain-specific similarities over individual attributes. The record-linkage problem arises naturally in the context of data cleansing that usually precedes data analysis and mining. Since the scalability issue of record linkage was addressed in [21], the repertoire of database techniques dealing with multidimensional data sets has significantly increased. Specifically, many effective and efficient approaches for distance-preserving transforms and similarity joins have been developed. Based on these advances, we explore a novel approach to record linkage. For each attribute of records, we first map values to a multidimensional Euclidean space that preserves domain-specific similarity. Many mapping algorithms can be applied, and we use the Fastmap approach [16] as an example. Given the merging rule that defines when two records are similar based on their attribute-level similarities, a set of attributes are chosen along which the merge will proceed. A multidimensional similarity join over the chosen attributes is used to find similar pairs of records. Our extensive experiments using real data sets show that our solution has very good efficiency and recall.
10617810
Integrated Requirement Selection and Scheduling for the Release Planning of a Software Product
This paper investigates two integer linear programming models that integrate requirement scheduling into software release planning. The first model can schedule the development of the requirements for the new release exactly in time so that the project span is minimized and the resource and precedence constraints are satisfied. The second model is for combined requirement selection and scheduling, which can not only maximize revenues but also calculates an on-time-delivery project schedule simultaneously. Two simulations are presented to examine the influence of precedence constraints and compare the differences of the traditional prioritization models and the two new ones. The simulation results suggest that requirement dependency can significantly influence the project plan and the combined model for requirement selection and scheduling is better in the sense of efficiency and on-time delivery.
2501834
On the security of the Yen-Guo's domino signal encryption algorithm (DSEA)
Recently, a new domino signal encryption algorithm (DSEA) was proposed for digital signal transmission, especially for digital images and videos. This paper analyzes the security of DSEA, and points out the following weaknesses: (1) its security against the brute-force attack was overestimated; (2) it is not sufficiently secure against ciphertext-only attacks, and only one ciphertext is enough to get some information about the plaintext and to break the value of a sub-key; (3) it is insecure against known/chosen-plaintext attacks, in the sense that the secret key can be recovered from a number of continuous bytes of only one known/chosen plaintext and the corresponding ciphertext. Experimental results are given to show the performance of the proposed attacks, and some countermeasures are discussed to improve DSEA.
46337154
Minimum cross entropy thresholding
Abstract The threshold selection problem is solved by minimizing the cross entropy between the image and its segmented version. The cross entropy is formulated in a pixel-to-pixel basis between the two images and a computationally attractive algorithm employing the histogram is developed. Without making a priori assumptions about the population distribution, this method provides an unbiased estimate of a binarized version of the image in an information theoretic sense.