No abstract

As a typical, discrete, and NP-hard problem, assembly sequence planning (ASP) has direct impact on assembly quality and costs. So far, lots of graph-based and meta-heuristic approaches cannot solve this problem effectively. This paper proposes an effective ASP algorithm based on the harmony search (HS) algorithm, which has an outstanding global search ability to obtain the global optimum more efficiently. To solve the ASP problem, an improved harmony search (IHS) algorithm is proposed mainly in four aspects: (1) an encoding of harmony is designed based on ASP problems; (2) an initial harmony memory (HM) is established using the opposition-based learning (OBL) strategy; (3) a particular way to improvise a new harmony is developed; and (4) a local search strategy is introduced to accelerate the convergence speed. Finally, the advantage of the proposed ASP algorithm over the competing algorithms in solving ASP problems is verified by two experiments. Moreover, the proposed ASP algorithm is applied to a practical problem, a propeller of azimuth thruster to verify its practicability.

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With the development of advanced manufacturing technology, more and more enterprises utilize automated guided vehicles to transfer materials for computer numerical control machines in the workshop. Because automated guided vehicle scheduling problem is non-deterministic polynomial-hard, highly efficient automated guided vehicle scheduling algorithms are necessary to improve productivity of the workshop. In order to solve this problem, a mathematical model with a new objective function is established firstly, which incorporates two indicators, that is, the standard deviation of the waiting time of computer numerical control material buffers and the total travel distance of automated guided vehicle, reflecting the overall capacity of computer numerical control machines and the energy efficiency of automated guided vehicles during the actual production, respectively. Then, an improved harmony search algorithm is proposed, which includes an effective discrete encoding scheme of harmony, a new initialization method for harmony memory based on opposition-based learning strategy, a dynamic harmony memory considering rate parameter and a local search strategy. The property of the proposed algorithm is evaluated through three cases from the real-world manufacturing system for producing back cover of smart phone. Compared with the competing algorithms, the results demonstrate the superiority of proposed algorithm for solving automated guided vehicle scheduling problem obviously.