39,672 research outputs found
Multi-objective discrete particle swarm optimisation algorithm for integrated assembly sequence planning and assembly line balancing
In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set
Sharp-edged geometric obstacles in microfluidics promote deformability-based sorting of cells
Sorting cells based on their intrinsic properties is a highly desirable
objective, since changes in cell deformability are often associated with
various stress conditions and diseases. Deterministic lateral displacement
(DLD) devices offer high precision for rigid spherical particles, while their
success in sorting deformable particles remains limited due to the complexity
of cell traversal in DLDs. We employ mesoscopic hydrodynamics simulations and
demonstrate prominent advantages of sharp-edged DLD obstacles for probing
deformability properties of red blood cells (RBCs). By consecutive sharpening
of the pillar shape from circular to diamond to triangular geometry, a
pronounced cell bending around an edge is achieved, serving as a deformability
sensor. Bending around the edge is the primary mechanism, which governs the
traversal of RBCs through such DLD device. This strategy requires an
appropriate degree of cell bending by fluid stresses, which can be controlled
by the flow rate, and exhibits good sensitivity to moderate changes in cell
deformability. We expect that similar mechanisms should be applicable for the
development of novel DLD devices that target intrinsic properties of many other
cells.Comment: 16 pages, 9 figure
Element Distinctness, Frequency Moments, and Sliding Windows
We derive new time-space tradeoff lower bounds and algorithms for exactly
computing statistics of input data, including frequency moments, element
distinctness, and order statistics, that are simple to calculate for sorted
data. We develop a randomized algorithm for the element distinctness problem
whose time T and space S satisfy T in O (n^{3/2}/S^{1/2}), smaller than
previous lower bounds for comparison-based algorithms, showing that element
distinctness is strictly easier than sorting for randomized branching programs.
This algorithm is based on a new time and space efficient algorithm for finding
all collisions of a function f from a finite set to itself that are reachable
by iterating f from a given set of starting points. We further show that our
element distinctness algorithm can be extended at only a polylogarithmic factor
cost to solve the element distinctness problem over sliding windows, where the
task is to take an input of length 2n-1 and produce an output for each window
of length n, giving n outputs in total. In contrast, we show a time-space
tradeoff lower bound of T in Omega(n^2/S) for randomized branching programs to
compute the number of distinct elements over sliding windows. The same lower
bound holds for computing the low-order bit of F_0 and computing any frequency
moment F_k, k neq 1. This shows that those frequency moments and the decision
problem F_0 mod 2 are strictly harder than element distinctness. We complement
this lower bound with a T in O(n^2/S) comparison-based deterministic RAM
algorithm for exactly computing F_k over sliding windows, nearly matching both
our lower bound for the sliding-window version and the comparison-based lower
bounds for the single-window version. We further exhibit a quantum algorithm
for F_0 over sliding windows with T in O(n^{3/2}/S^{1/2}). Finally, we consider
the computations of order statistics over sliding windows.Comment: arXiv admin note: substantial text overlap with arXiv:1212.437
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