On Selecting and Scheduling Assembly Plans Using Constraint Programming

This work presents the application of Constraint Programming to the problem of selecting and sequencing assembly operations. The set of all feasible assembly plans for a single product is represented using an And/Or graph. This representation embodies some of the constraints involved in the planning problem, such as precedence of tasks, and the constraints due to the completion of a correct assembly plan. The work is focused on the selection of tasks and their optimal ordering, taking into account their execution in a generic multi-robot system. In order to include all different constraints of the problem, the And/Or graph representation is extended, so that links between nodes corresponding to assembly tasks are added, taking into account the resource constraints. The resultant problem is mapped to a Constraint Satisfaction Problem (CSP), and is solved using Constraint Programming, a powerful programming paradigm that is increasingly used to model and solve many hard real-life problems

A Genetic Algorithm for Assembly Sequence Planning

This work presents a genetic algorithm for assembly sequence planning. This problem is more difficult than other sequencing problems that have already been tackled with success using these techniques, such as the classic Traveling Salesperson Problem (TSP) or the Job Shop Scheduling Problem (JSSP). It not only involves the arranging of tasks, as in those problems, but also the selection of them from a set of alternative operations. Two families of genetic operators have been used for searching the whole solution space. The first includes operators that search for new sequences locally in a predetermined assembly plan, that of parent chromosomes. The other family of operators introduces new tasks in the solution, replacing others to maintain the validity of chromosomes, and it is intended to search for sequences in other assembly plans. Furthermore, some problem-based heuristics have been used for generating the individuals in the population

Searching a bitstream in linear time for the longest substring of any given density

Given an arbitrary bitstream, we consider the problem of finding the longest substring whose ratio of ones to zeroes equals a given value. The central result of this paper is an algorithm that solves this problem in linear time. The method involves (i) reformulating the problem as a constrained walk through a sparse matrix, and then (ii) developing a data structure for this sparse matrix that allows us to perform each step of the walk in amortised constant time. We also give a linear time algorithm to find the longest substring whose ratio of ones to zeroes is bounded below by a given value. Both problems have practical relevance to cryptography and bioinformatics.Comment: 22 pages, 19 figures; v2: minor edits and enhancement

Commitment and Slack for Online Load Maximization

We consider a basic admission control problem in which jobs with deadlines arrive online and our goal is to maximize the total volume of executed job processing times. We assume that the deadlines have a slack of at least ϵ, that is, each deadline d satisfies d≥ (1+ϵ)· p+r with processing time p and release date r. In addition, we require the admission policy to support immediate commitment, that is, upon a job's submission, we must immediately make the decision of if and where we schedule the job, and this decision is irreversible. Our main contribution is a deterministic algorithm with nearly optimal competitive ratio for load maximization on multiple machines in the non-preemptive model. Previous results either only held for a single machine, did not support commitment, or required job preemption and migration

Enhancing location privacy for electric vehicles (at the right time)

An electric vehicle is a promising and futuristic automobile propelled by electric motor(s), using electrical energy stored in batteries or another energy storage device. Due to the need of battery recharging, the cars will be required to visit recharging infrastructure very frequently. This may disclose the users\u27 private information, such as their location, which may expose users\u27 privacy. In this paper, we provide mechanisms to enhance location privacy of electric vehicles at the right time, by proposing an anonymous payment system with privacy protection support. Our technique further allows traceability in the case where the cars are stolen. 2012 Springer-Verlag