A common assumption in the literature on mixed-model assembly line balancing is that a task that is common to multiple models must be assigned to a single station. In this paper, we relax this restriction, and allow a common task to be assigned to different stations for different models. We seek to minimize the sum of costs of the stations and the task duplication. We develop an optimal solution procedure based on a backtracking branch-and-bound algorithm and evaluate its performance via a large set of experiments. A branch-and-bound based heuristic is then developed for solving large-scale problems. The heuristic solutions are compared with a lower bound and experiments show that the heuristic provides much better solutions than those obtained by traditional approaches. ?? 2005 Elsevier B.V. All rights reserved.
We investigated analytically and numerically the interplay between two opposing forms of synaptic plasticity: positive-feedback, long-term potentiation/depression (LTP/LTD), and negative-feedback, homeostatic synaptic plasticity (HSP). A detailed model of a CA1 pyramidal neuron, with numerous HSP-modifiable dendritic synapses, demonstrates that HSP may have an important role in selecting which spatial patterns of LTP/LTD are to last. Several measures are developed for predicting the net residual potentiation/depression after HSP from the initial spatial pattern of LTP/LTD. Under a local dendritic HSP mechanism, sparse patterns of LTP/LTD, which we show, using information theoretical tools, to have a significant impact on the output of the postsynaptic neuron, will persist. In contrast, spatially clustered patterns with a smaller impact on the output will diminish. A global somatic HSP mechanism, conversely, will favor distally occurring LTP/LTDs over proximal ones. Despite the negative-feedback nature of HSP, under both local and global HSP, numerous synaptic potentiations/depressions can persist. These experimentally testable results imply that HSP could be significantly involved in shaping the spatial distribution of synaptic weights in the dendrites and not just normalizing it, as is currently believed.
Homeostatic synaptic plasticity (HSP) is an important mechanism attributed with the slow regulation of the neuron's activity. Whenever activity is chronically enhanced, HSP weakens the weights of the synapses in the dendrites and vice versa. Because dendritic morphology and its electrical properties partition the dendritic tree into functional compartments, we set out to explore the interplay between HSP and dendritic compartmentalization. For this purpose, we used a detailed model of a CA1 pyramidal neuron receiving a large number of activity-dependent plastic synapses and developed a novel approach for specifying functional dendritic subunits. We found that the degree of dendritic compartmentalization and the location-specificity of HSP are strongly tied. A local HSP mechanism, operating at the level of the individual synapse, will regard the neuron as a multiunit distributed system, each unit consisting of many synapses, and will thus support dendritic compartmentalization, whereas a global HSP mechanism, modifying all synapses in unison, will treat the neuron as a single centralized unit. Both local and global HSP can successfully counterbalance persistent, cell-wide perturbations of dendritic activity. The spatial distribution of synaptic weights throughout the dendrites will markedly differ under the local versus global HSP mechanisms. We suggest an experimental paradigm to unravel which type of HSP mechanism operates in the dendritic tree. The answer to this question will have important implications to our understanding of the functional organization of the neuron.
