Relevant bibliographies by topics / Additive heuristic

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Additive heuristic'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Additive heuristic"

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Felner, A., R. E. Korf, and S. Hanan. "Additive Pattern Database Heuristics." Journal of Artificial Intelligence Research 22 (November 1, 2004): 279–318. http://dx.doi.org/10.1613/jair.1480.

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We explore a method for computing admissible heuristic evaluation functions for search problems. It utilizes pattern databases, which are precomputed tables of the exact cost of solving various subproblems of an existing problem. Unlike standard pattern database heuristics, however, we partition our problems into disjoint subproblems, so that the costs of solving the different subproblems can be added together without overestimating the cost of solving the original problem. Previously, we showed how to statically partition the sliding-tile puzzles into disjoint groups of tiles to compute an ad
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Younes, H. L. S., and R. G. Simmons. "VHPOP: Versatile Heuristic Partial Order Planner." Journal of Artificial Intelligence Research 20 (December 1, 2003): 405–30. http://dx.doi.org/10.1613/jair.1136.

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VHPOP is a partial order causal link (POCL) planner loosely based on UCPOP. It draws from the experience gained in the early to mid 1990's on flaw selection strategies for POCL planning, and combines this with more recent developments in the field of domain independent planning such as distance based heuristics and reachability analysis. We present an adaptation of the additive heuristic for plan space planning, and modify it to account for possible reuse of existing actions in a plan. We also propose a large set of novel flaw selection strategies, and show how these can help us solve more pro
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Bennette, Elizabeth, Frank C. Keil, and Sami R. Yousif. "A Ubiquitous Illusion of Volume: Are Impressions of 3D Volume Captured by an “Additive Heuristic”?" Perception 50, no. 5 (2021): 462–69. http://dx.doi.org/10.1177/03010066211003746.

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Several empirical approaches have attempted to explain perception of 2D and 3D size. While these approaches have documented interesting perceptual effects, they fail to offer a compelling, general explanation of everyday size perception. Here, we offer one. Building on prior work documenting an “Additive Area Heuristic” by which observers estimate perceived area by summing objects’ dimensions, we show that this same principle—an “additive heuristic”—explains impressions of 3D volume. Observers consistently discriminate sets that vary in “additive volume,” even when there is no true difference;
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Laroche, Michel, Chankon Kim, and Takayoshi Matsui. "Which decision heuristics are used in consideration set formation?" Journal of Consumer Marketing 20, no. 3 (2003): 192–209. http://dx.doi.org/10.1108/07363760310472236.

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This study empirically investigates consumers’ use of five heuristics (conjunctive, disjunctive, lexicographic, linear additive, and geometric compensatory) in the consideration set formation, a critical first phase before actual choice behavior. Data were collected on the selection of beer brands and fast food outlets by real consumers. Using a decomposition approach in determining the consumers’ choice heuristics, it was found that the conjunctive heuristic is the most often used decision model in the consideration set formation for the two product classes. Implications for brand managers an
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Yang, F., J. Culberson, R. Holte, U. Zahavi, and A. Felner. "A General Theory of Additive State Space Abstractions." Journal of Artificial Intelligence Research 32 (July 1, 2008): 631–62. http://dx.doi.org/10.1613/jair.2486.

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Informally, a set of abstractions of a state space S is additive if the distance between any two states in S is always greater than or equal to the sum of the corresponding distances in the abstract spaces. The first known additive abstractions, called disjoint pattern databases, were experimentally demonstrated to produce state of the art performance on certain state spaces. However, previous applications were restricted to state spaces with special properties, which precludes disjoint pattern databases from being defined for several commonly used testbeds, such as Rubik's Cube, TopSpin and t
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Katz, M., and C. Domshlak. "Implicit Abstraction Heuristics." Journal of Artificial Intelligence Research 39 (September 21, 2010): 51–126. http://dx.doi.org/10.1613/jair.3063.

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State-space search with explicit abstraction heuristics is at the state of the art of cost-optimal planning. These heuristics are inherently limited, nonetheless, because the size of the abstract space must be bounded by some, even if a very large, constant. Targeting this shortcoming, we introduce the notion of (additive) implicit abstractions, in which the planning task is abstracted by instances of tractable fragments of optimal planning. We then introduce a concrete setting of this framework, called fork-decomposition, that is based on two novel fragments of tractable cost-optimal planning
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Nguyen, Tung Duc, Kien Quang Nguyen, and Ruck Thawonmas. "Heuristic Search Exploiting Non-additive and Unit Properties for RTS-game Unit Micromanagement." Journal of Information Processing 23, no. 1 (2015): 2–8. http://dx.doi.org/10.2197/ipsjjip.23.2.

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Yousif, Sami R., and Frank C. Keil. "The Additive-Area Heuristic: An Efficient but Illusory Means of Visual Area Approximation." Psychological Science 30, no. 4 (2019): 495–503. http://dx.doi.org/10.1177/0956797619831617.

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How do we determine how much of something is present? A large body of research has investigated the mechanisms and consequences of number estimation, yet surprisingly little work has investigated area estimation. Indeed, area is often treated as a pesky confound in the study of number. Here, we describe the additive-area heuristic, a means of rapidly estimating visual area that results in substantial distortions of perceived area in many contexts, visible even in simple demonstrations. We show that when we controlled for additive area, observers were unable to discriminate on the basis of true
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Aloui, Aymen, and Khaled Hadj-Hamou. "A heuristic approach for a scheduling problem in additive manufacturing under technological constraints." Computers & Industrial Engineering 154 (April 2021): 107115. http://dx.doi.org/10.1016/j.cie.2021.107115.

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ITO, K. "Involvement, in-group message, and persuasiveness : The additive effect of heuristic and systematic processing." Japanese Journal of Personality 11, no. 1 (2002): 52–53. http://dx.doi.org/10.2132/jjpjspp.11.1_52.

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Dissertations / Theses on the topic "Additive heuristic"

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Keyder, Emil Ragip. "New Heuristics for Planning with Action Costs." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7570.

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Classical planning is the problem of nding a sequence of actions that take an agent from an initial state to a desired goal situation, assuming deter- ministic outcomes for actions and perfect information. Satis cing planning seeks to quickly nd low-cost solutions with no guarantees of optimality. The most e ective approach for satis cing planning has proved to be heuristic search using non-admissible heuristics. In this thesis, we introduce several such heuristics that are able to take into account costs on actions, and there- fore try to minimize the more general metric of cost, rat
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Hansson, Erik. "Temporal Task and Motion Plans: Planning and Plan Repair : Repairing Temporal Task and Motion Plans Using Replanning with Temporal Macro Operators." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152722.

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This thesis presents an extension to the Temporal Fast Downward planning system that integrates motion planning in it and algorithms for generating two types of temporal macro operators expressible in PDDL2.1. The extension to the Temporal Fast Downward planning system includes, in addition to the integration of motion planning itself, an extension to the context-enhanced additive heuristic that uses information from the motion planning part to improve the heuristic estimate. The temporal macro operators expressible in PDDL2.1 are, to the author's knowledge, an area that is not studied within
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Yang, Fan. "Additive abstraction-based heuristics." Phd thesis, 2011. http://hdl.handle.net/10048/1749.

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In this thesis, we study theoretically and empirically the additive abstraction-based heuristics. First we present formal general definitions for abstractions that extend to general additive abstractions. We show that the general definition makes proofs of admissibility, consistency, and additivity easier, by proving that several previous methods for defining abstractions and additivity satisfy three imple conditions. Then we investigate two general methods for defining additive abstractions and run experiments to determine the effectiveness of these methods for two benchmark state spaces: Top
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Chen, Chien-Min, and 陳健民. "A Heuristic of an Additive Intuitionistic Fuzzy Preference Relation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/7r4aak.

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碩士<br>國立高雄應用科技大學<br>工業工程與管理系碩士在職專班<br>106<br>This paper considers the problem of Wang(2013) additive intuitionistic fuzzy preference relation. For the additive inconsistent intuitionistic fuzzy preference relation, using the least squares optimization model and goal programming optimization model, we obtain the priority vector. If the individual priority vector is the same as that of social, we obtain the collective priority vector via goal programming optimization model. For the additive consistent intuitionistic fuzzy preference relation satisfying Tanino(1984), we present the explicit formu
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Books on the topic "Additive heuristic"

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Deruelle, Nathalie, and Jean-Philippe Uzan. The radiation reaction force. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786399.003.0037.

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This chapter observes the reaction force acting on a charge due to the radiation it emits. It also considers the related questions of renormalization and physical interpretation. Modifying the Lorentz equation introduced in Chapter 11 by including a radiation reaction force provides a heuristic method of describing the expected slowing of an accelerated charge in response to the radiation it emits. The chapter then goes on to describe the Abraham–Lorentz–Dirac reaction force, the counter-effect of the radiation of an accelerated charge on its motion. In addition, the chapter shows that a hydro
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Cavalcante Passos, Ives, and Flávio Kapczinski. Staging and neuroprogression in bipolar disorder: treatment implications. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198748625.003.0024.

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It is known that if, not all, a substantial proportion of patients with bipolar disorder (BD) present a progressive course with functional and cognitive impairment. In addition, patients with BD and multiple mood episodes have a worse response to lithium and cognitive behaviour therapy. However, many current treatment guidelines do not take these clinical features that change with illness progression into account. In order to clarify these clinical questions, the term ‘neuroprogression’ was conceptualized as the pathological rewiring of the brain that takes place in parallel with the clinical
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Heffer, Chris. All Bullshit and Lies? Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190923280.001.0001.

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In a post-factual world in which claims are often held to be true only to the extent that they partisanly confirm one’s preexisting beliefs, this book asks the following crucial questions: How can one identify the many forms of untruthfulness in discourse? How can one know when their use is ethically wrong? How can one judge untruthfulness in the messiness of situated discourse? Drawing on pragmatics, philosophy, psychology, and law, All Bullshit and Lies? develops a comprehensive framework for analyzing untruthful discourse in situated context. The TRUST (Trust-Related Untruthfulness in Situa
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Book chapters on the topic "Additive heuristic"

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Eyerich, Patrick, Robert Mattmüller, and Gabriele Röger. "Using the Context-Enhanced Additive Heuristic for Temporal and Numeric Planning." In Springer Tracts in Advanced Robotics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25116-0_6.

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Li, Qiang, David Zhang, Ibrahim Kucukkoc, and Naihui He. "Heuristic Techniques for Real-Time Order Acceptance and Scheduling in Metal Additive Manufacturing." In Mathematical Modelling and Optimization of Engineering Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37062-6_1.

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Sridharan, R., and Vinay V. Panicker. "Ant Colony Algorithm for Single Stage Supply Chain." In Encyclopedia of Business Analytics and Optimization. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5202-6.ch014.

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Swarm intelligence has emerged as an approach for developing meta-heuristics to solve combinatorial optimization problems. Ant Colony Optimization (ACO) is an example for a swarm-intelligence based meta-heuristic inspired by the social behavior of colonies of ants. In this chapter, an ACO-based heuristic is proposed for solving a distribution-allocation problem in a single-stage of a supply chain. Thus, this work aims at modeling and analysis of the distribution-allocation problem in a single-stage supply chain with a fixed cost for a transportation route. In addition, it provides an insight for researchers in developing heuristics based on ant colony optimization for supply chain related problems.
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Sridharan, R., and Vinay V. Panicker. "Ant Colony Algorithm for Two Stage Supply Chain." In Encyclopedia of Business Analytics and Optimization. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-5202-6.ch015.

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This chapter focuses on the distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The supply chain considered in this research consists of suppliers, distributors and customers. Each transportation route is associated with a fixed charge (or a fixed cost) and a transportation cost per unit transported. The presence of this fixed cost makes the problem difficult to solve. This motivates the researchers to develop heuristics based on non-traditional optimization techniques that can provide near-optimal solutions in reasonable time. In this research, an ant colony optimization based heuristic is proposed to solve a distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The comparative analysis carried out in this study reveals that the solutions obtained using proposed heuristic are better than those obtained using an existing heuristic in terms of total cost and computational time. In addition, special emphasis is placed in developing heuristics based on ant colony optimization for solving supply chain related problems and identifying opportunities for further research in this area.
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Karegowda, Asha Gowda, and Devika G. "Meta-Heuristic Parameter Optimization for ANN and Real-Time Applications of ANN." In Applications of Artificial Neural Networks for Nonlinear Data. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4042-8.ch010.

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Artificial neural networks (ANN) are often more suitable for classification problems. Even then, training of ANN is a surviving challenge task for large and high dimensional natured search space problems. These hitches are more for applications that involves process of fine tuning of ANN control parameters: weights and bias. There is no single search and optimization method that suits the weights and bias of ANN for all the problems. The traditional heuristic approach fails because of their poorer convergence speed and chances of ending up with local optima. In this connection, the meta-heuristic algorithms prove to provide consistent solution for optimizing ANN training parameters. This chapter will provide critics on both heuristics and meta-heuristic existing literature for training neural networks algorithms, applicability, and reliability on parameter optimization. In addition, the real-time applications of ANN will be presented. Finally, future directions to be explored in the field of ANN are presented which will of potential interest for upcoming researchers.
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Karegowda, Asha Gowda, and Devika G. "Meta-Heuristic Parameter Optimization for ANN and Real-Time Applications of ANN." In Research Anthology on Artificial Neural Network Applications. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch008.

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Artificial neural networks (ANN) are often more suitable for classification problems. Even then, training of ANN is a surviving challenge task for large and high dimensional natured search space problems. These hitches are more for applications that involves process of fine tuning of ANN control parameters: weights and bias. There is no single search and optimization method that suits the weights and bias of ANN for all the problems. The traditional heuristic approach fails because of their poorer convergence speed and chances of ending up with local optima. In this connection, the meta-heuristic algorithms prove to provide consistent solution for optimizing ANN training parameters. This chapter will provide critics on both heuristics and meta-heuristic existing literature for training neural networks algorithms, applicability, and reliability on parameter optimization. In addition, the real-time applications of ANN will be presented. Finally, future directions to be explored in the field of ANN are presented which will of potential interest for upcoming researchers.
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Ghedjati, Fatima, and Safa Khalouli. "A Hybrid Meta-Heuristic to Solve a Multi-Criteria HFS Problem." In Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch009.

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In this chapter the authors address a hybrid flow shop scheduling problem considering the minimization of the makespan in addition to the sum of earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, to deal with this problem, the authors propose a method which consists on the one hand, on using a meta-heuristic based on ant colony optimization algorithm to generate feasible solutions and, on the other hand, on using an aggregation multi-criteria method based on fuzzy logic to assist the decision-maker to express his preferences according to the considered objective functions. The aggregation method uses the Choquet integral. This latter allows to take into account the interactions between the different criteria. Experiments based on randomly generated instances were conducted to test the effectiveness of the approach.
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Goodridge, Wayne S., Shyamala C. Sivakumar, William Robertson, and William J. Phillips. "Multiple Optimization of Network Carrier and Traffic Flow Goals Using a Heuristic Routing Decision System." In Intelligent Quality of Service Technologies and Network Management. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-791-6.ch007.

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This chapter presents a multiple constraint optimization algorithm called routing decision system (RDS) that uses the concept of preference functions to address the problem of selecting paths in core networks that satisfy traffic-oriented QoS requirements while simultaneously satisfying network resource-oriented performance goals. The original contribution lies in the use of strong scales employed for constructing a multiple criteria preference function in an affine space. The use of preference functions makes it possible for paths that match both traffic-oriented and resource-oriented goals to be selected by the algorithm. The RDS algorithm is used in conjunction with a heuristic path finding algorithm called Constraint Path Heuristic (CP-H) algorithm which is a novel approach to finding a set of constraint paths between source and destination nodes in a network. The CP-H algorithm finds multiple paths for each metric and then passes all the paths to the RDS algorithm. Simulation results showed that the CP-H/RDS algorithm has a success rate of between 93 and 96% when used in Waxman graph topologies, and is shown to be significantly better than other heuristic based algorithms under strict constraints. In addition, it is shown that the associated execution time of the CP-H/RDS algorithm is slightly higher than other heuristic based algorithms but good enough for use in an online traffic engineering (TE) application. Simulations to assess the performance of CP-H/RDS algorithm in a TE environment show that the algorithms has lower call block rates than other TE algorithms. It is also shown that the CP-H/RDS has a 96% probability of providing at least two distinct feasible backup paths in addition to the main QoS path. A framework for implementing the CP-H/RDS as a routing server is proposed. The routing decision system server (RDSS) framework is novel in that the complexity introduced by QoS awareness remains outside the network.
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Issa, Mohamed, and Aboul Ella Hassanien. "Multiple Sequence Alignment Optimization Using Meta-Heuristic Techniques." In Handbook of Research on Machine Learning Innovations and Trends. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2229-4.ch018.

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Sequence alignment is a vital process in many biological applications such as Phylogenetic trees construction, DNA fragment assembly and structure/function prediction. Two kinds of alignment are pairwise alignment which align two sequences and Multiple Sequence alignment (MSA) that align sequences more than two. The accurate method of alignment is based on Dynamic Programming (DP) approach which suffering from increasing time exponentially with increasing the length and the number of the aligned sequences. Stochastic or meta-heuristics techniques speed up alignment algorithm but with near optimal alignment accuracy not as that of DP. Hence, This chapter aims to review the recent development of MSA using meta-heuristics algorithms. In addition, two recent techniques are focused in more deep: the first is Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO). The second is Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm (MO-BFO).
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Issa, Mohamed, and Aboul Ella Hassanien. "Multiple Sequence Alignment Optimization Using Meta-Heuristic Techniques." In Data Analytics in Medicine. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1204-3.ch031.

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Sequence alignment is a vital process in many biological applications such as Phylogenetic trees construction, DNA fragment assembly and structure/function prediction. Two kinds of alignment are pairwise alignment which align two sequences and Multiple Sequence alignment (MSA) that align sequences more than two. The accurate method of alignment is based on Dynamic Programming (DP) approach which suffering from increasing time exponentially with increasing the length and the number of the aligned sequences. Stochastic or meta-heuristics techniques speed up alignment algorithm but with near optimal alignment accuracy not as that of DP. Hence, This chapter aims to review the recent development of MSA using meta-heuristics algorithms. In addition, two recent techniques are focused in more deep: the first is Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO). The second is Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm (MO-BFO).
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Conference papers on the topic "Additive heuristic"

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Fan, Gaojian, Martin Müller, and Robert Holte. "Additive Merge-and-Shrink Heuristics for Diverse Action Costs." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/599.

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In many planning applications, actions can have highly diverse costs. Recent studies focus on the effects of diverse action costs on search algorithms, but not on their effects on domain-independent heuristics. In this paper, we demonstrate there are negative impacts of action cost diversity on merge-and-shrink (M&amp;S), a successful abstraction method for producing high-quality heuristics for planning problems. We propose a new cost partitioning method for M&amp;S to address the negative effects of diverse action costs. We investigate non-unit cost IPC domains, especially those for which div
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Blösch-Paidosh, Alexandra, Saeema Ahmed-Kristensen, and Kristina Shea. "Evaluating the Potential of Design for Additive Manufacturing Heuristic Cards to Stimulate Novel Product Redesigns." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97865.

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Abstract Additive manufacturing (AM) affords those who wield it correctly the benefits of shape, material, hierarchical, and functional complexity. However, many engineers and designers lack the training and experience necessary to take full advantage of these benefits. They require training, tools, and methods to assist them in gaining the enhanced design freedom made possible by additive manufacturing. This work, which is an extension of the authors’ previous work, explores if design heuristics for AM, presented in a card-based format, are an effective mechanism for helping designers achieve
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Stewart, Bradley, and Chelsea White. "Heuristic search with multiple criteria and additive cost structure." In 26th IEEE Conference on Decision and Control. IEEE, 1987. http://dx.doi.org/10.1109/cdc.1987.272567.

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Xu, Peng, Xiling Yao, Lequn Chen, Kui Liu, and Guijun Bi. "Heuristic Kinematics of a Redundant Robot-Positioner System for Additive Manufacturing." In 2020 6th International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2020. http://dx.doi.org/10.1109/iccar49639.2020.9108047.

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Li, Dongxu, Enrico Scala, Patrik Haslum, and Sergiy Bogomolov. "Effect-Abstraction Based Relaxation for Linear Numeric Planning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/665.

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This paper studies an effect-abstraction based relaxation for reasoning about linear numeric planning problems. The effect-abstraction decomposes non-constant linear numeric effects into actions with conditional effects over additive constant numeric effects. With little effort, on this compiled version, it is possible to use known subgoaling based relaxations and relative heuristics. The combination of these two steps leads to a novel relaxation based heuristic. Theoretically, the relaxation is proved tighter than previous interval based relaxation and leading to safe-pruning heuristics. Empi
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Chua, Ping Chong, Seung Ki Moon, and Yen Ting Ng. "Multi-Objective Implementation of Additive Manufacturing in Make-to-Stock Production." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22085.

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Abstract As additive manufacturing (AM) develops and matures over the years, it has reached a stage where implementation into a conventional production system becomes possible. With additive manufacturing currently suitable for product personalization/high customization yet small volume production, there are various ways of implementation in a conventional production line. This aim of this paper is to explore the implementation of additive manufacturing in a complementary manner to process internal job orders of large quantities in make-to-stock (MTS) production. Splitting of production orders
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Oh, Yosep, Sara Behdad, and Chi Zhou. "Part Separation Methods for Assembly Based Design in Additive Manufacturing." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-68002.

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The goal of this study is to develop a heuristic part separation algorithm for assembly-based design in Additive Manufacturing (AM). The objective is to minimize the total processing time including both buildup time and assembly time. In the proposed algorithm, the part separation is recursively conducted until the number of assemblies reaches a threshold value. The proposed method helps designers determine the proper number of assemblies and their buildup orientations. A numerical example is provided to illustrate the application of the algorithm.
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Jiang, Zhengqian, Sean Psulkowski, Arriana Nwodu, Hui Wang, and Tarik Dickens. "Improved Co-Scheduling of Printing Path Scanning for Collaborative Additive Manufacturing." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-3005.

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Abstract Additive manufacturing processes, especially those based on fused filament fabrication (FFF) mechanism, have relatively low productivity and suffer from production scalability issue. One solution is to adopt a collaborative additive manufacturing system that is equipped with multiple extruders working simultaneously to improve productivity. The collaborative additive manufacturing encounters a grand challenge in the scheduling of printing path scanning by different extruders. If not properly scheduled, the extruders may collide into each other or the structures built by earlier schedu
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Oh, Yosep, Chi Zhou, and Sara Behdad. "Production Planning for Mass Customization in Additive Manufacturing: Build Orientation Determination, 2D Packing and Scheduling." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85639.

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The efficient production planning of Additively Manufactured (AM) parts is a key point for industry-scale adoption of AM. This study develops an AM-based production plan for the case of manufacturing a significant number of parts with different shapes and sizes by multiple machines with the ultimate purpose of reducing the cycle time. The proposed AM-based production planning includes three main steps: (1) determination of build orientation; (2) 2D packing of parts within the limited workspace of AM machines; and (3) scheduling parts on multiple AM machines. For making decision about build ori
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Blösch-Paidosh, Alexandra, and Kristina Shea. "Preliminary User Study on Design Heuristics for Additive Manufacturing." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85908.

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Additive manufacturing (AM) has unique capabilities when compared to traditional manufacturing, such as shape, hierarchical, functional, and material complexity, a fact that has fascinated those in research, industry, and the media for the last decade. Consequently, designers would like to know how they can incorporate AM’s special capabilities into their designs, but are often at a loss as to how to do so. Design for Additive Manufacturing (DfAM) methods are currently in development but the vast majority of existing methods are not tailored to the needs and knowledge of designers in the early
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Reports on the topic "Additive heuristic"

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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-c
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