Addressing an integrated decision-making structure for planting and harvesting scheduling may lead to more realistic, accurate, and efficient decision in fresh product supply chain. This study aims to develop an integrated bi-objective tactical and operational planning model for producing and distributing fresh crops. The first objective of the model is to maximize total revenue of supply chain...

This paper presents an analysis of the spatial resolution properties of tomographic image reconstruction based on a regularized least-squares objective function. The derivations are based on an idealized space-invariant tomographic system having a continuum of radial and angular samples. The analysis accounts for mismatch between the true radial point-spread function (PSF) of the measurements a...

When the weight of each attribute is determined in the multiple attribute decision making problems, calculated by the method of subjective values or objective values solely will cause the problem that weight coefficient is not reasonable. So the paper puts forward the weightingmethod which is based on maximizing deviations and normalized constraint condition. The method integrates the subjectiv...

This paper proposes a new methodology to solve multiobjective optimization problems by invoking genetic algorithms and the concept of Shapley values cooperative games. It is well known that Pareto-optimal solutions can be obtained solving corresponding weighting are formulated assigning some suitable weights objective functions. In this paper, we game from original problem regarding functions a...

We introduce a weight update formula that is expressed only in terms of firing rates and their derivatives and that results in changes consistent with those associated with spike-timing dependent plasticity (STDP) rules and biological observations, even though the explicit timing of spikes is not needed. The new rule changes a synaptic weight in proportion to the product of the presynaptic firi...

This paper presents a new approach to discrete choice analysis for risky prospects. Conventional discrete choice analysis focuses on riskless prospects and does not deal with the scenario where the alternatives that the decision-makers choose from are associated with risk. In this paper, we investigate decisionmakers’ risk perception and choice behaviour in choice experiments when they are faci...

The context-tree weighting algorithm [4] is a universal source coding algorithm for binary tree sources. In [2] the algorithm is modified for byte-oriented tree sources. This paper describes the context-tree branch-weighting algorithm, which can reduce the number of parameters for such sources, without increasing the complexity significantly.

The CHaracteristic-function-Enabled Source Separation (CHESS) method for independent component analysis (ICA) is based on approximate joint diagonalization (AJD) of Hessians of the observations’ empirical log-characteristicfunction, taken at selected off-origin “processing points”. As previously observed in other contexts, the AJD performance can be significantly improved by optimal weighting, ...

In response to the uncertainty, nonlinearity and open-loop instability of active magnetic levitation control system, and neural network PID quadratic optimal controller are designed using optimum control theory. Introducing supervised Hebb learning rule, constraint control for positioning errors and control increment weighting are realized by adjusting weighting coefficients, using weighed sum-...

In this paper we propose a generic framework for the optimization of image feature encoders for image retrieval. Our approach uses a triplet-based objective that compares, for a given query image, the similarity scores of an image with a matching and a non-matching image, penalizing triplets that give a higher score to the non-matching image. We use stochastic gradient descent to address the re...