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Knowledge amplification by structured expert randomization—KASERs in SoS design
Published in Mo Jamshidi, Systems of Systems Engineering, 2017
The use of heuristics can sacrifice admissibility (i.e., the guarantee of finding an optimal solution if one exists), but gains several orders of magnitude in the capability to solve otherwise intractable problems. Often, heuristic power can be gained by sacrificing admissibility by using some function for h that is not a lower bound on h*. An example pertaining to the use of nonadmissible heuristics can be found in Nilsson’s 15-puzzle [11]. Here, h(n) = P(n) + 3 S(n), where P(n) is the sum of the distances that each tile is from “home” (ignoring intervening pieces), and S(n) is a sequence score obtained by checking around the noncentral squares in turn, allotting two for every tile not followed by its proper successor and allotting zero for every other tile; a piece in the center scores one [11]. Other heuristics include, but are not limited to simulated annealing, exploiting domain symmetries, scaling from small to large, divide and conquer, problem reduction, as well as other transformational approaches.
A “Push-Pull” rearrangement while routing for a driverless delivery vehicle
Published in Cogent Engineering, 2019
Samir Tetouani, Abdelssamad Chouar, Jamal Lmariouh, Aziz Soulhi, Jamila Elalami
The customer is guided by a “voice” which provides the instructions to follow when unloading/loading “Smart-Boxes” (See Figure 1(b)). The centralized control task is to re-arrange “Smart-Boxes” (while driving between two Delivery/Pickup Points) on the grid into a desired goal state. The structure for sliding the “Smart-Boxes” is constituted a rectangular grid (5 × 10 cells) with square conveyor modules (Figure 2(a)). Each module (called “Flex-conveyor” (Ballot et al., 2012): is a “Right-Angle-Transfer” able to slide the “Smart-Box” in the four directions (Left (L), Right (R), Up (U), and Down (D)) if the neighboring location is empty. The idea is derived from the 15-puzzle shown in Figure 2(b) (Gue & Kim, 2007).
A color image encryption scheme using customized map
Published in The Imaging Science Journal, 2023
Nadeem Iqbal et al. [1] have presented a new image encryption based on chaotic systems and DNA computing. A cryptosystem implemented with the chaotic map, DNA, cellular automaton, 15-puzzle, knight, Rubik's cube, Magic square, Nine palace, king chess piece, hybrid chaotic map, and other supporting approaches is used to ensure image security. The method employs swapping operations at both the pixel and DNA levels. Swapping a randomly selected pixel from the input array scrambles the image. The chaotic and scrambled images are combined in an XOR procedure to get the final image. The scheme simulation results exhibit good resistance to statistical, differential, and key space analysis. A chaos and DNA-based image encryption system was created by Xingyuan Wang and Chuanming Liu [2]. The PWLCM chaotic map is used first to generate the key image pixels. Next, the plain image and key image are encoded with the DNA rule, and the respective image rows are encoded with the logistic map. The scheme has the ability to withstand all types of attacks for secure data transmission. Xingyuan Wang and Lin Liu [3] have presented an image encryption method based on DNA substitution and hash table scrambling. A hyper chaotic Chen system is used to produce a pseudorandom sequence. Two randomly generated sequences that are non-repeated are used to permute pixels in the procedure. The encoding rule and DNA substitution are then used for diffusion. High key sensitivity and strong anti-attack capabilities are also features of the resulting encrypted image. Jan Sher Khan et al. [4] proposed selective image encryption with increased efficiency. The SHA-512 hash technique and the random DNA sequence are produced using the chaotic map.
An optimal and a heuristic algorithm for the single-item retrieval problem in puzzle-based storage systems with multiple escorts
Published in International Journal of Production Research, 2019
Altan Yalcin, Achim Koberstein, Kai-Oliver Schocke
A PBS system with only one escort also resembles the classical 15-puzzle game on a grid and its related generalisations on an grid (Demaine 2001). While the goal of these puzzles is to bring tiles in a desired order, in PBS the order of tiles is not relevant but instead one aims to bring one item to a desired location (with the minimum possible number of moves). Ratner and Warmuth (1986) showed that it is NP-hard to find a solution using the fewest number of moves from a given configuration. It can be shown that the hardest instances of a 15-puzzle are solvable using at most 80 slides (Brüngger et al. 1999). The number of possible states in an n-puzzle is n!, whereas the number of solvable configurations is n! / 2 (Korf 1999). Thus, the 8-puzzle contains states, the 15-puzzle states and the 24-puzzle states. The 8-puzzle can be solved using the A* search algorithm (Hart, Nilsson, and Raphael 1968), where the search-guiding heuristic is the sum of the Manhattan distances of each block from its goal position. Korf (1985) stated that the memory requirement of A* search exceeded the available memory at that time to solve the 15-puzzle, which motivated the development of the more memory-efficient IDA* algorithm. However, IDA* was not able to find solutions for the 24-puzzle in a reasonable time. For this purpose, Hansson, Mayer, and Yung (1992) proposed an improvement with a more accurate heuristic than the Manhattan distance.