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Journal articles on the topic 'Knapsack'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Malitsky, Yuri, Meinolf Sellmann, and Radoslaw Szymanek. "Filtering Bounded Knapsack Constraints in Expected Sublinear Time." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 141–46. http://dx.doi.org/10.1609/aaai.v24i1.7560.

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We present a highly efficient incremental algorithm for propagating bounded knapsack constraints. Our algorithm is based on the sublinear filtering algorithm for binary knapsack constraints by Katriel et al. and achieves similar speed-ups of one to two orders of magnitude when compared with its linear-time counterpart. We also show that the representation of bounded knapsacks as binary knapsacks leads to ineffective filtering behavior. Experiments on standard knapsack benchmarks show that the new algorithm significantly outperforms existing methods for handling bounded knapsack constraints.

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2

Osipyan, V. O., A. S. Zhuk, E. P. Lukashchik, K. I. Litvinov, and R. Kh Bagdasaryan. "Multiplicative knapsack injectivity as condition of effective unauthorized access protection." Journal of Physics: Conference Series 2131, no. 2 (2021): 022084. http://dx.doi.org/10.1088/1742-6596/2131/2/022084.

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Abstract The mathematical modelling of data protection systems based on multiplicative knapsack is considered. In particular, development of cryptographic solution to hierarchic access control problem is represented. Previously in research the authors has formulated the requirements to knapsack in order to apply these to a hierarchic access control problem based on the requirements for similar models. Here in the article the possibility of practical implementation of the construction of such knapsacks is pointed. Based on special mathematical model for multiplicative knapsacks generalized suff

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3

Aho, Isto. "Interactive Knapsacks." Fundamenta Informaticae 44, no. 1-2 (2000): 1–23. https://doi.org/10.3233/fun-2000-441-201.

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The interactive knapsack problems are generalizations of the classical knapsack problem. Three different new NP-complete problems, interactive knapsack heuristic decision problem (IKHD), interactive knapsack decision problem (IKD) and multidimensional cloned knapsack decision problem (MDCS), are presented for the interactive knapsack models. IKD and MDCS are shown to be strongly NP-complete. By using interactive knapsacks we can model many planning and scheduling problems in an innovative way. Possible application areas include electricity management, single and multiprocessor scheduling, and

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4

Sur, Giwon, Shun Yuel Ryu, JongWon Kim, and Hyuk Lim. "A Deep Reinforcement Learning-Based Scheme for Solving Multiple Knapsack Problems." Applied Sciences 12, no. 6 (2022): 3068. http://dx.doi.org/10.3390/app12063068.

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A knapsack problem is to select a set of items that maximizes the total profit of selected items while keeping the total weight of the selected items no less than the capacity of the knapsack. As a generalized form with multiple knapsacks, the multi-knapsack problem (MKP) is to select a disjointed set of items for each knapsack. To solve MKP, we propose a deep reinforcement learning (DRL) based approach, which takes as input the available capacities of knapsacks, total profits and weights of selected items, and normalized profits and weights of unselected items and determines the next item to

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Devita, Riri Nada, and Aji Prasetya Wibawa. "Teknik-teknik Optimasi Knapsack Problem." Sains, Aplikasi, Komputasi dan Teknologi Informasi 2, no. 1 (2020): 35. http://dx.doi.org/10.30872/jsakti.v2i1.3299.

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Optimasi merupakan sebuah teknik yang identik dengan memaksimalkan sumber daya yang terbatas. Salah satunya adalah permasalahan nyata yang memperlukan teknik optimasi adalah cara mengatur barang-barang yang dimuat dalam suatu knapsack (karung/ Tas). Knapsack problem merupakan masalah dimana orang dihadapkan pada persoalan optimasi pemilihan benda yang dapat di tampung ke dalam sebuah knapsack (karung) yang memiliki keterbatasan daya dan ruang tampung. Oleh karena itu, dengan adanya optimasi dalam pemilihan barang yang akan ditampung dalam knapsak tersebut diharapkan dapat menghasilkan efisiens

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6

Sun, Bo, Ali Zeynali, Tongxin Li, Mohammad Hajiesmaili, Adam Wierman, and Danny H. K. Tsang. "Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (2022): 67–68. http://dx.doi.org/10.1145/3543516.3456271.

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We introduce and study a general version of the fractional online knapsack problem with multiple knapsacks, heterogeneous constraints on which items can be assigned to which knapsack, and rate-limiting constraints on the assignment of items to knapsacks. This problem generalizes variations of the knapsack problem and of the one-way trading problem that have previously been treated separately, and additionally finds application to the real-time control of electric vehicle (EV) charging. We introduce a new algorithm that achieves a competitive ratio within an additive factor of the best achievab

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7

Chen, Kai, and Sheldon M. Ross. "STATIC STOCHASTIC KNAPSACK PROBLEMS." Probability in the Engineering and Informational Sciences 29, no. 4 (2015): 527–46. http://dx.doi.org/10.1017/s0269964815000170.

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Two stochastic knapsack problem (SKP) models are considered: the static broken knapsack problem (BKP) and the SKP with simple recourse and penalty cost problem. For both models, we assume: the knapsack has a constant capacity; there are n types of items and each type has an infinite supply; a type i item has a deterministic reward vi and a random weight with known distribution Fi. Both models have the same objective to maximize expected total return by finding the optimal combination of items, that is, quantities of items of each type to be put in knapsack. The difference between the two model

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8

Rizzi, Romeo, and Luca Nardin. "Polynomial Time Instances for the IKHO Problem." ISRN Electronics 2012 (April 8, 2012): 1–10. http://dx.doi.org/10.5402/2012/859820.

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The Interactive Knapsacks Heuristic Optimization (IKHO) problem is a particular knapsacks model in which, given an array of knapsacks, every insertion in a knapsack affects also the other knapsacks, in terms of weight and profit. The IKHO model was introduced by Isto Aho to model instances of the load clipping problem. The IKHO problem is known to be APX-hard and, motivated by this negative fact, Aho exhibited a few classes of polynomial instances for the IKHO problem. These instances were obtained by limiting the ranges of two structural parameters, c and u, which describe the extent to which

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9

Buayen, Patcharin, and Jeeraporn Werapun. "Efficient 0/1-Multiple-Knapsack Problem Solving by Hybrid DP Transformation and Robust Unbiased Filtering." Algorithms 15, no. 10 (2022): 366. http://dx.doi.org/10.3390/a15100366.

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The multiple knapsack problem (0/1-mKP) is a valuable NP-hard problem involved in many science-and-engineering applications. In current research, there exist two main approaches: 1. the exact algorithms for the optimal solutions (i.e., branch-and-bound, dynamic programming (DP), etc.) and 2. the approximate algorithms in polynomial time (i.e., Genetic algorithm, swarm optimization, etc.). In the past, the exact-DP could find the optimal solutions of the 0/1-KP (one knapsack, n objects) in O(nC). For large n and massive C, the unbiased filtering was incorporated with the exact-DP to solve the 0

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10

Sun, Bo, Lin Yang, Mohammad Hajiesmaili, et al. "The Online Knapsack Problem with Departures." Proceedings of the ACM on Measurement and Analysis of Computing Systems 6, no. 3 (2022): 1–32. http://dx.doi.org/10.1145/3570618.

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The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, we study a general version that includes item departures, while also considering multiple knapsacks and multi-dimensional item sizes. We design a threshold-based online algorithm and prove that the algorithm can achieve order-optimal competitive ratios. Beyond worst-case performance guarantees, we also aim to achieve near-optimal average perfor

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Sun, Bo, Lin Yang, Mohammad Hajiesmaili, et al. "The Online Knapsack Problem with Departures." ACM SIGMETRICS Performance Evaluation Review 51, no. 1 (2023): 59–60. http://dx.doi.org/10.1145/3606376.3593576.

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The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, we study a general version that includes item departures, while also considering multiple knapsacks and multi-dimensional item sizes. We design a threshold-based online algorithm and prove that the algorithm can achieve order-optimal competitive ratios. Beyond worst-case optimized algorithms, we also propose a data-driven online algorithm that

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12

Wang, Ziqian, Xin Huang, Yan Zhang, et al. "Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance." Mathematics 12, no. 22 (2024): 3538. http://dx.doi.org/10.3390/math12223538.

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The knapsack problem is a typical bi-objective combinatorial optimization issue, wherein maximizing the value of the packed items is achieved concurrently with minimizing the weight of the load. Due to the conflicting objectives of the knapsack problem and the typical discrete property of the items involved, swarm intelligence algorithms are commonly employed. The diversity of optimal combinations in the knapsack problem has become a focal point, which involves finding multiple packing solutions at the same value and weight. For this purpose, this paper proposes a Multi-Objective Equilibrium O

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Murin, D. M. "The Order in the Growth of the Injective and Super-Increasing Vectors Knapsacks Quantity." Modeling and Analysis of Information Systems 19, no. 3 (2015): 124–35. http://dx.doi.org/10.18255/1818-1015-2012-3-124-135.

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In 1978 R. Mercle and M. Hellman offered to use the subset sum problem for constructing cryptographic systems. The proposed cryptosystems were based on a class of the knapsacks with super-increasing vectors. This class is a subset of the set of knapsacks with injective (cryptographic) vectors that allow the single-valued decoding (decryption) result. In this paper we consider the problems related to the order in the growth of the injective vectors knapsacks quantity and to the order in the growth of knapsacks quantity with the super-increasing vectors through the knapsack maximal element incre

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Santoso, Dewi Agustini, Ifan Rizqa, Diana Aqmala, and Farrikh Alzami. "Optimizing Parcel Package Selection Using an Enhanced Multiple Knapsack Problem Approach with Greedy Dynamic Programming." Moneter: Jurnal Keuangan dan Perbankan 12, no. 3 (2024): 526–35. http://dx.doi.org/10.32832/moneter.v12i3.996.

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This study introduces an enhanced algorithm for solving the Multiple Knapsack Problem to optimize parcel package selection, particularly focusing on balancing value maximization with price and weight constraints. Due to Dynamic Programming requires significant memory, The proposed method employs a heuristic approach such as greedy algorithm, initially sorting items by their value-to-weight ratio and iteratively filling each knapsack to maximize total value while adhering to constraints. The algorithm demonstrates high computational efficiency, solving instances within 0.07 seconds, and achieve

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15

Anwar, Zahra Zharifah, and Caturiyati Caturiyati. "OPTIMASI MASALAH KNAPSACK 0-1 DENGAN MENGGUNAKAN PEMROGRAMAN DINAMIS." Jurnal Kajian dan Terapan Matematika 11, no. 1 (2025): 64–72. https://doi.org/10.21831/jktm.v11i1.22844.

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Optimasi merupakan aspek yang mendasar dalam pengambilan keputusan, di mana tujuannya adalah untuk mengidentifikasi solusi optimal dari sekumpulan alternatif yang kompleks. Contoh masalah sehari-hari yang memerlukan optimasi adalah masalah pemuatan barang (masalah knapsack), yang berdampak langsung pada efisiensi operasi logistik dan pada akhirnya berpengaruh pada biaya operasional. Salah satu variasi utama dalam masalah knapsack adalah masalah knapsack 0-1. Setiap item pada masalah knapsack 0-1 memiliki pilihan untuk dimuat ke dalam knapsack atau tidak. Masalah knapsack 0-1 merupakan masalah

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Agusfrianto, Fakhry Asad, and Ramya Rachmawati. "Perbandingan Metode Branch and Bound dan Enumerasi implisit dalam menyelesaikan masalah Knapsack." AKSIOMA : Jurnal Matematika dan Pendidikan Matematika 13, no. 1 (2022): 64–74. http://dx.doi.org/10.26877/aks.v13i1.11782.

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Masalah knapsack merupakan masalah program bilangan bulat yang melibatkan satu kendala saja. Masalah knapsack umumnya diilustrasikan dengan suatu tas dan barang. Masalah yang akan kita selesaikan dalam masalah knapsack adalah memaksimumkan harga barang dengan kapasitas tertentu yang dapat dimuat oleh tas dengan kapasitas tertentu juga. Dalam menyelesaikan masalah knapsack, umumnya dapat dikerjakan secara langsung (penerkaan), menggunakan metode branch and bound, dan enumerasi implisit. Pada paper ini, akan dilakukan perbandingan penyelesaian masalah knapsack dengan metode branch and bound dan

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Aminudin, Aminudin, Ahmad Faisal Helmi, and Sofyan Arifianto. "Analisa Kombinasi Algoritma Merkle-Hellman Knapscak dan Logaritma Diskrit pada Aplikasi Chat." Jurnal Teknologi Informasi dan Ilmu Komputer 5, no. 3 (2018): 325. http://dx.doi.org/10.25126/jtiik.201853844.

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<p class="Judul2">Informasi melalui jaringan internet sangat rentan terhadap penyadapan oleh pihak yang tidak bertanggung jawab. Agar informasi tersebut aman, maka dibutuhkan teknik kriptografi untuk melindungi dan mengamankan informasi tersebut. Salah satu contoh algoritma kriptografi yang dapat digunakan untuk mengamankan informasi adalah algoritma Merkle-Hellman Knapsack. Akan tetapi, algoritma ini sudah dinyatakan tidak aman karena sudah dapat dipecahkan oleh Shamir (1984). Beberapa tahun terakhir muncul perkembangan dari algoritma knapsack yaitu kombinasi algoritma knapsack dan loga

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Xiao, Meng, and Yun Yao Zhou. "Discussion on Knapsack Problem Optimization Algorithm Based on Complex Network." Applied Mechanics and Materials 556-562 (May 2014): 3354–56. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3354.

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This passage is to put forward knapsack problem optimization algorithm based on complex network (KOABCN). Knapsack problem has extremely wide application in a great number of fields. For instance, knapsack problem can be applied in information coding, budget control, project choosing, material cutting, cargo loading and unloading as well as Internet information safety. Since 1950’s, knapsack problem has been one of the most heated topics in algorithm and complexity research. Therefore, knapsack will still be largely focused in the next period of research.

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Hu, Zhi Jun, and Rong Li. "Ant Colony Optimization Algorithm for the 0-1 Knapsack Problem Based on Genetic Operators." Advanced Materials Research 230-232 (May 2011): 973–77. http://dx.doi.org/10.4028/www.scientific.net/amr.230-232.973.

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0-1 knapsack problem is a typical combinatorial optimization question in the design and analysis of algorithms. The mathematical description of the knapsack problem is given in theory. The 0-1 knapsack problem is solved by ant colony optimistic algorithm that is improved by introducing genetic operators. To solve the 0-1 knapsack problem with the improved ant colony algorithm, experimental results of numerical simulations, compared with greedy algorithm and dynamic programming algorithm, have shown obvious advantages in efficiency and accuracy on the knapsack problem.

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Hassan, Yosra Ali, and Ibrahim Mahmood Ibrahim. "Review on Algorithmic Approaches to Solving Knapsack Problem." Asian Journal of Research in Computer Science 18, no. 3 (2025): 314–24. https://doi.org/10.9734/ajrcos/2025/v18i3595.

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The knapsack problem is a classic optimization challenge where the objective is to maximize the total value of items packed into a knapsack without exceeding its weight capacity It comes in several variants, including the 0–1 Knapsack Problem (0-1KP), the Multidimensional Knapsack Problem (MDKP), and the Quadratic Knapsack Problem (QKP). This Review paper conducts a detailed exploration and analysis of algorithmic strategies developed for solving the knapsack problem (KP). The paper delves into various algorithmic approaches, including advanced dynamic programming, heuristic and metaheuristic

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Dang, Binh Thanh, and Tung Khac Truong. "Binary salp swarm algorithm for discounted {0-1} knapsack problem." PLOS ONE 17, no. 4 (2022): e0266537. http://dx.doi.org/10.1371/journal.pone.0266537.

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While the classical knapsack problem has been the object to be solved by optimization algorithm proposals for many years, another version of this problem, discounted {0-1} knapsack problem, is gaining a lot of attention recently. The original knapsack problem requires selecting specific items from an item set to maximize the total benefit while ensuring that the total weight does not exceed the knapsack capacity. Meanwhile, discounted {0-1} knapsack problem has more stringent requirements in which items are divided into groups, and only up to one item from a particular group can be selected. T

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Fluschnik, Till, Piotr Skowron, Mervin Triphaus, and Kai Wilker. "Fair Knapsack." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1941–48. http://dx.doi.org/10.1609/aaai.v33i01.33011941.

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We study the following multiagent variant of the knapsack problem. We are given a set of items, a set of voters, and a value of the budget; each item is endowed with a cost and each voter assigns to each item a certain value. The goal is to select a subset of items with the total cost not exceeding the budget, in a way that is consistent with the voters’ preferences. Since the preferences of the voters over the items can vary significantly, we need a way of aggregating these preferences, in order to select the socially best valid knapsack. We study three approaches to aggregating voters’ prefe

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Bampis, Evripidis, Bruno Escoffier, and Alexandre Teiller. "Multistage knapsack." Journal of Computer and System Sciences 126 (June 2022): 106–18. http://dx.doi.org/10.1016/j.jcss.2022.01.002.

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Clark, Nancy. "Knapsack Nutrition." Physician and Sportsmedicine 21, no. 9 (1993): 21–22. http://dx.doi.org/10.1080/00913847.1993.11710412.

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Rahul, Vaddadi Sai, N. Narayanan Prasanth, and S. P. Raja. "A Recursive and Parallelized Dynamic Programming Implementation of Hard Merkle-Hellman Knapsack System for Public Key Cryptography." Cybernetics and Information Technologies 21, no. 2 (2021): 58–69. http://dx.doi.org/10.2478/cait-2021-0019.

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Abstract Merkle-Hellman public key cryptosystem is a long-age old algorithm used in cryptography. Despite being computationally fast, for very large input sizes it may operate slower due to thread creation overhead or reaching a deadlock situation. In this paper, we discuss the working principles of the Traditional Merkle-Hellman knapsack cryptosystem, which is an Easy knapsack. The challenges of Hard Knapsack and how it overcomes the shortcomings of the Traditional Easy Knapsack, are also discussed. The Hard knapsack variant of Merkle-Hellman is solved first using plain recursion and then imp

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Pattiasina, Timothy John. "Rancang Bangun Aplikasi Enkripsi dan Dekripsi Email Dengan Menggunakan Algoritma Advanced Encryption Standard Dan Knapsack." Teknika 3, no. 1 (2014): 1–10. http://dx.doi.org/10.34148/teknika.v3i1.15.

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Advanced Encryption Standard (AES) dan Knapsack adalah dua algoritma enkripsi simetris dan asimetris yang paling sering digunakan. Penelitian ini menganalisa kedua algoritma AES dan algoritma Knapsack. Prototipe aplikasi enkripsi email ini dirancang dengan menggabungkan karateristik algoritma AES dan Knapsack untuk memecahkan masalah keamanan email. Algoritma AES digunakan untuk mengenkripsi dan deskripsi email berupa teks atau file, sedangkan Algoritma Knapsack di gunakan untuk mengenkripsi kunci AES. Enkripsi hybrid yang diterapkan pada aplikasi bertujuan untuk menambah keamanan informasi da

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Azwar, Nurul Azri, Parapat Gultom, and Sawaluddin Sawaluddin. "Discrete Optimization Model in Constructing Optimal Decision Tree." SinkrOn 7, no. 3 (2022): 2108–15. http://dx.doi.org/10.33395/sinkron.v7i3.11592.

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Decision trees have been well studied and widely used in knowledge discovery and decision support systems. One of the applications of binary integer programming to form decision trees or decision making is the knapsack problem. The knapsack problem is an integer programming problem that involves only one constraint. The knapsack problem is generally illustrated with a bag and an item. The problem to be solved is to maximize the price of goods with a certain capacity that can be loaded by a bag with a certain capacity too. In solving the knapsack problem, it can generally be done directly. In t

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R, Iwan Fitrianto, and Djoko Soetarno. "MENENTUKAN LINTASAN TERPENDEK (SHORTEST PATH) DENGAN 0/1 KNAPSACK PROBLEM DAN PENDEKATAN ALGORITMA DYNAMIC PROGRAMMING." CCIT Journal 4, no. 3 (2011): 293–315. http://dx.doi.org/10.33050/ccit.v4i3.449.

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Knapsack merupakan salah satu permasalahan klasik yang banyak ditemukan di kehidupan sehari-hari. Knapsack dapat diartikan sebagai karung atau kantung. Karung digunakan untuk memuat sesuatu dan tentunya tidak semua objek dapat ditampung di dalam karung. Karung tersebut hanya dapat menyimpan beberapa objek dengan total ukurannya lebih kecil atau sama dengan ukuran kapasitas karung. Pada prinsipnya masalah Knapsack ini adalah masalah optimalisasi sehingga algoritma harus mencari sebuah solusi paling optimal sebagai jawabannya. Tulisan ini akan membahas bagaimana menyelesaikan 0/1 Knapsack Proble

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Hertrich, Christoph, and Martin Skutella. "Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (2021): 7685–93. http://dx.doi.org/10.1609/aaai.v35i9.16939.

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The development of a satisfying and rigorous mathematical understanding of the performance of neural networks is a major challenge in artificial intelligence. Against this background, we study the expressive power of neural networks through the example of the classical NP-hard Knapsack Problem. Our main contribution is a class of recurrent neural networks (RNNs) with rectified linear units that are iteratively applied to each item of a Knapsack instance and thereby compute optimal or provably good solution values. We show that an RNN of depth four and width depending quadratically on the profi

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Khalaf, Rifaat Z., Hamza B. Habib, and Thakwan Akram Jawad. "Attacking the Knapsack Public-key Cryptosystem." Webology 19, no. 1 (2022): 5302–9. http://dx.doi.org/10.14704/web/v19i1/web19356.

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Merkle–Hellman knapsack cryptosystem is a public-key cryptosystem, which means, two keys are used, a public key for the encryption and a private key for the decryption. This cryptosystem is not secure against the cryptosystem attacks, such as LLL Algorithm. In this paper, we introduce a new study to attack the knapsack problem. This study is based on discussing certain facts regarding the public key to extract the multiplier. Also, based on some facts we can find the modulus that is used in the cryptosystem. Therefore, the experimental outcome shows that this method is easier and faster to att

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Chauhan, Pinkey, Millie Pant, and Kusum Deep. "Gompertz PSO variants for Knapsack and Multi-Knapsack Problems." Applied Mathematics-A Journal of Chinese Universities 36, no. 4 (2021): 611–30. http://dx.doi.org/10.1007/s11766-021-4583-y.

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Zhu, Nan. "A relation between the knapsack and group knapsack problems." Discrete Applied Mathematics 87, no. 1-3 (1998): 255–68. http://dx.doi.org/10.1016/s0166-218x(98)00061-4.

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Letchford, Adam N., and Georgia Souli. "Lifting the knapsack cover inequalities for the knapsack polytope." Operations Research Letters 48, no. 5 (2020): 607–11. http://dx.doi.org/10.1016/j.orl.2020.07.010.

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Wu, Jou Tung, and Jiun Yu Tu. "COMPARE EFFICACY BETWEEN KNAPSACK SPRAYER AND UAV SPRAYER APPLICATION IN CHEMICAL SPRAYING: A CASE STUDY OF GARLAND CHRYSANTHEMUM." International Journal of Agriculture and Environmental Research 09, no. 03 (2023): 342–80. http://dx.doi.org/10.51193/ijaer.2023.9307.

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In the field of pesticide spraying for crop diseases and insect pests, the deposition structure of pesticide droplet includes coverage rate, droplet diameter, and droplet coverage density, which is one of the most important factors affecting the spraying effect. In this study, two spraying devices, knapsack sprayer and unmanned aerial vehicle (UAV), were used to spray twice on the leaf front and back of Garland Chrysanthemum, the relevant parameters were obtained, and the effects of spraying and pest control were evaluated by WaterSensitive Paper and Sticky Insect Paper. This study is expected

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Khanpara, B. M., and R. K. Kathiria. "Development and performance evaluation of picking mechanism for knapsack cotton picker." INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES 19, no. 1 (2023): 145–52. http://dx.doi.org/10.15740/has/ijas/19.1/145-152.

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One of the most significant fibre cash crops in both India and the rest of the world is cotton (Gossypium herbaceum). India is the world’s second-largest cotton producer. Cotton is hand-picked by human labours in India, which is a laborious and time-consuming task. In existing knapsack cotton picker, the cotton quality was compromised due to the impact of the impeller vanes during conveying of picked cotton to collector. Keeping all these aspects in mind, a picking mechanism for knapsack power driven cotton picker was developed with considering the agronomical parameters, functional requiremen

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Hou, Wenjun, and Marek Perkowski. "Quantum-based algorithm and circuit design for bounded Knapsack optimization problem." Quantum Information and Computation 20, no. 9&10 (2020): 766–86. http://dx.doi.org/10.26421/qic20.9-10-4.

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The Knapsack Problem is a prominent problem that is used in resource allocation and cryptography. This paper presents an oracle and a circuit design that verifies solutions to the decision problem form of the Bounded Knapsack Problem. This oracle can be used by Grover Search to solve the optimization problem form of the Bounded Knapsack Problem. This algorithm leverages the quadratic speed-up offered by Grover Search to achieve a quantum algorithm for the Knapsack Problem that shows improvement with regard to classical algorithms. The quantum circuits were designed using the Microsoft Q# Progr

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Bramantya, Devan, I. Gede Santi Astawa, I. Wayan Supriana, Luh Gede Astuti, Ngurah Agus Sanjaya ER, and I. Gusti Agung Gede Arya Kadyanan. "Rancangan dan Analisis Model Algoritma Genetika Untuk Menyelesaikan Permasalahan Knapsack 2 Dimensi." JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) 11, no. 2 (2022): 395. http://dx.doi.org/10.24843/jlk.2022.v11.i02.p18.

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The knapsack problem is problem that is still often found in everyday life, one of which is the problem of selecting goods to be transported into containers for delivery of goods. This knapsack problem can be solved by using various optimization algorithms, one of which is the genetic algorithm. This study aims to design a genetic algorithm model to solve the 2-dimensional knapsack problem. 2-dimensional knapsack problem is a knapsack problem that has 2 constraints and in this study, the constraints used were weight and volume.. The evaluation results of the genetic algorithm will be compared

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Bosov, A. A., A. V. Gоrbоvа, and N. V. Khalipova. "Substantiation of a heuristic algorithm in the knapsack problem." Science and Transport Progress, no. 42 (December 25, 2012): 170–75. http://dx.doi.org/10.15802/stp2012/9390.

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Introduction: Formed knapsack problem in terms of set functions and is a heuristic algorithm. The goal: to prove that the heuristic algorithm is essential. Some facts from [2]. The equivalence of the limit order to E.Borelyu and convergence in measure. The theorem about the need to set a maximum of function. The situation is quite the algorithm: We present three cases where a heuristic algorithm is sufficient. Counterexample: An Rear take from [1], and given the addition heuristic algorithm, which allows to obtain the solution of the knapsack problem. Vector optimization: With the knapsack pro

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Mubarak, Altamimi, and Ramaha Nehad. "0-1 Knapsack Problem Solving using Genetic Optimization Algorithm." Engineering and Technology Journal 9, no. 07 (2024): 4412–26. https://doi.org/10.5281/zenodo.12820192.

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A 0-1 knapsack problem with m constraints is known as the 0-1 multidimensional knapsack problem, and it is challenging to solve using standard techniques like branch and bound algorithms or dynamic programming. The goal of the Knapsack problem is to maximize the utility of the items in a knapsack while staying within its carrying capacity. This paper presents a genetic algorithm with Python code that can solve publicly available instances of the multidimensional knapsack problem in a very quick computational time. By identifying the significant genes, the attribute reduction method that uses t

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Regita, Yulia Dewi, Kiswara Agung Santoso, and Ahmad Kamsyakawuni. "Algoritma Elephant Herding Optimization: Permasalahan Multiple Constraints Knapsack 0-1." Majalah Ilmiah Matematika dan Statistika 18, no. 1 (2018): 13. http://dx.doi.org/10.19184/mims.v18i1.17241.

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Optimization problems are often found in everyday life, such as when determining goods to be a limited storage media. This causes the need for the selection of goods in order to obtain profits with the requirements met. This problem in mathematics is usually called a knapsack. Knapsack problem itself has several variations, in this study knapsack type used is multiple constraints knapsack 0-1 which is solved using the Elephant Herding Optimization (EHO) algorithm. The aim of this study is to obtain an optimal solution and study the effectiveness of the algorithm comparing it to the Simplex met

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Yanasse, Horacio Hideki, Nei Yoshihiro Soma, and Nelson Maculan. "An algorithm for determining the K-best solutions of the one-dimensional Knapsack problem." Pesquisa Operacional 20, no. 1 (2000): 117–34. http://dx.doi.org/10.1590/s0101-74382000000100011.

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In this work we present an enumerative scheme for determining the K-best solutions (K > 1) of the one dimensional knapsack problem. If n is the total number of different items and b is the knapsack's capacity, the computational complexity of the proposed scheme is bounded by O(Knb) with memory requirements bounded by O(nb). The algorithm was implemented in a workstation and computational tests for varying values of the parameters were performed.

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Ghadi, Yazeed Yasin, Tamara AlShloul, Zahid Iqbal Nezami, et al. "An efficient optimizer for the 0/1 knapsack problem using group counseling." PeerJ Computer Science 9 (April 14, 2023): e1315. http://dx.doi.org/10.7717/peerj-cs.1315.

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The field of optimization is concerned with determining the optimal solution to a problem. It refers to the mathematical loss or gain of a given objective function. Optimization must reduce the given problem’s losses and disadvantages while maximizing its earnings and benefits. We all want optimal or, at the very least, suboptimal answers because we all want to live a better life. Group counseling optimizer (GCO) is an emerging evolutionary algorithm that simulates the human behavior of counseling within a group for solving problems. GCO has been successfully applied to single and multi-object

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Selvi, V. "Clustering Analysis of Greedy Heuristic Method in Zero_One Knapsack Problem." International Journal of Emerging Research in Management and Technology 6, no. 7 (2018): 39. http://dx.doi.org/10.23956/ijermt.v6i7.181.

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Knapsack problem is a surely understood class of optimization problems, which tries to expand the profit of items in a knapsack without surpassing its capacity, Knapsack can be solved by several algorithms such like Greedy, dynamic programming, Branch & bound etc. The solution to the zero_one knapsack problem (KP) can be viewed as the result of a sequence of decision. Clustering is the process of resolving that type of applications. Different clustering application for grouping elements with equal priority. In this paper we are introducing greedy heuristic algorithm for solving zero_one kn

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Locatelli, Tamara, Silvério de Paiva Freitas, Ismael Lourenço de Jesus Freitas, et al. "Deposition, Endo-drift and Exo-drift in the Pulverization in Coffee With Different Equipment." Journal of Agricultural Science 11, no. 17 (2019): 187. http://dx.doi.org/10.5539/jas.v11n17p187.

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The objective was to evaluate the equipment efficiency in reducing drift and increasing the spray deposition. The experiment was conducted of the conilon coffee plantation, located on the experimental area of the Federal Institute of Espirito Santo, Itapina, Brazil. The experiment was a randomized complete block design with four replications. The treatments consisted: a knapsack sprayer with electrostatic assistance, an electric knapsack sprayer, a knapsack sprayer with a spray shield, and a knapsack sprayer without a spray shield. All sprayers were equipped with a single spray nozzle. Spray d

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Kaliszewski, Ignacy, and Janusz Miroforidis. "Knapsack Balancing via Multiobjectivization." Applied Sciences 14, no. 20 (2024): 9236. http://dx.doi.org/10.3390/app14209236.

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In this paper, we address the aspect of knapsack balancing in the classic knapsack problem. Recognizing that excessive dispersion in the objective function or constraint coefficients of the optimal solution can be undesirable, we propose, when appropriate, to control this effect through problem multiobjectivization. By multiobjectivization, we mean the addition of one or more objective functions that aim to shift the original problem’s optimal solutions towards Pareto optimal solutions of the multiobjectivized problem, reducing the dispersion of the respective coefficients. We detail how the k

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Gong, Qiao Qiao, Yong Quan Zhou, and Yan Yang. "Artificial Glowworm Swarm Optimization Algorithm for Solving 0-1 Knapsack Problem." Advanced Materials Research 143-144 (October 2010): 166–71. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.166.

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In this paper, an artificial glowworm swarm optimization algorithm for solving 0-1 knapsack problem is proposed, and the detailed realization of the algorithm is illustrated. According to intelligent algorithm for knapsack problem, the question of sensitive parameter’s choice is avoided under the greed idea. Simulation results show that the artificial glowworm swarm optimization algorithm for solving 0-1 knapsack problems is feasible and effective.

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Abdullah, Rinaldy Ahmad, Abduh Riski, and Ahmad Kamsyakawuni. "PENERAPAN ALGORITMA PENGUINS SEARCH OPTIMIZATION (PeSOA) DAN ALGORITMA MIGRATING BIRDS OPTIMIZATION (MBO) PADA PERMASALAHAN KNAPSACK 0-1." Majalah Ilmiah Matematika dan Statistika 19, no. 2 (2019): 75. http://dx.doi.org/10.19184/mims.v19i2.17270.

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Every person would want maximum profit with as little as possible resources or capital. One example in everyday life is the problem of limited storage media but is required to get the maximum benefit. From this problem comes the term known as the knapsack problem. One of the problems with Knapsack is knapsack 0- 1, where knapsack 0-1 is a problem of storing goods where the item will be completely inserted or not at all. Completion of knapsack 0-1 problems can be helped using a metaheuristic algorithm. Metaheuristic algorithms include the Penguins Search Optimization (PeSOA) algorithm and the M

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Ping, Yuan, Baocang Wang, Shengli Tian, Jingxian Zhou, and Hui Ma. "PKCHD: Towards A Probabilistic Knapsack Public-Key Cryptosystem with High Density." Information 10, no. 2 (2019): 75. http://dx.doi.org/10.3390/info10020075.

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By introducing an easy knapsack-type problem, a probabilistic knapsack-type public key cryptosystem (PKCHD) is proposed. It uses a Chinese remainder theorem to disguise the easy knapsack sequence. Thence, to recover the trapdoor information, the implicit attacker has to solve at least two hard number-theoretic problems, namely integer factorization and simultaneous Diophantine approximation problems. In PKCHD, the encryption function is nonlinear about the message vector. Under the re-linearization attack model, PKCHD obtains a high density and is secure against the low-density subset sum atta

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Aho, Isto. "New polynomial-time instances to various knapsack-type problems." Fundamenta Informaticae 53, no. 3-4 (2002): 199–228. https://doi.org/10.3233/fun-2002-533-401.

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We describe a special case of the interactive knapsack optimization problem (motivated by the load clipping problem) solvable in polynomial time. Given an instance parameterized by k, the solution can be found in polynomial time, where the polynomial has degree k. In the interactive knapsack problem, $k$ is connected to the length induced by an item. A similar construction solves a special case of the 0–1 multi-dimensional knapsack and the 0–1 linear integer programming problems in polynomial time. In these problems the parameter determines the width of the restriction matrix, which is a band

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Novianti, Chofifah Alfin, Muhammad Khudzaifah, and Mohammad Nafie Jauhari. "Kriptografi Hibrida Cipher Block Chaining (CBC) dan Merkle-Hellman Knapsack untuk Pengamanan Pesan Teks." Jurnal Riset Mahasiswa Matematika 3, no. 1 (2023): 10–25. http://dx.doi.org/10.18860/jrmm.v3i1.22292.

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A secret message is a message that can only be seen by those who are entitled. In its delivery, a procedure is needed to keep the secret message secure, which is called cryptography. This research uses hybrid cryptography Cipher Block Chaining (CBC) and Merkle-Hellman Knapsack. The purpose of this research is to find out the encryption and decryption process of hybrid cryptography Cipher Block Chaining (CBC) and Merkle-Hellman Knapsack. The stages in this research use a qualitative approach with the library research method. In the encryption process with CBC, plaintext is encrypted first and t

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