https://bura.brunel.ac.uk/bitstream/2438/17829/4/FullText.pdf

Big data analytics in supply chain management: A state-of-the-art literature review

We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly, so we focus on heuristic methods that find locally optimal fits. The method we describe, which is a variation on the K-means algorithm for clustering, seems to work well in practice, at least on data that can be fit well by a convex function. We focus on the simplest function form, a maximum of a fixed number of affine functions, and then show how the methods extend to a more general form.

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Convex piecewise-linear fitting

In this paper, several kinds of invariant monotone maps and generalized invariant monotone maps are introduced. Some examples are given which show that invariant monotonicity and generalized invariant monotonicity are proper generalizations of monotonicity and generalized monotonicity. Relationships between generalized invariant monotonicity and generalized invexity are established. Our results are generalizations of those presented by Karamardian and Schaible.

Generalized invexity and generalized invariant monotonicity

On Properties of Preinvex Functions

Some quantum integral inequalities via preinvex functions

On Invex Sets and Preinvex Functions

Given a vertical block matrixA, we consider in this paper the generalized linear complementarity problem VLCP(q, A) introduced by Cottle and Dantzig. We formulate this problem as a linear complementarity problem with a square matrixM, a formulation which is different from a similar formulation given earlier by Lemke. Our formulation helps in extending many well-known results in linear complementarity to the generalized linear complementarity problem. We also show that the class of vertical block matrices which Cottle and Dantzig's algorithm can process is the same as the class of equivalent square matrices which Lemke's algorithm can process. We also present some degree-theoretic results on a vertical block matrix.

The generalized linear complementarity problem revisited

More on positive subdefinite matrices and the linear complementarity problem

On the classes of fully copositive and fully semimonotone matrices

Mathematical Programming and Its Applications in Finance Linear Programs with Totally Unimodular Coefficient Matrix Interior Point Method for Convex Quadratic Programming Analysis of Sets of Constraints, Traveling Salesman Problem and Tolerance-Based Algorithms Pedigree Polytope One-Defective Vertex Coloring Problem Complementarity Problem Fuzzy Twin Support Vector Machines for Pattern Classification Minimum Sum of Absolute Errors Regression Hedging Against the Market with No Short Selling Mathematical Programming and Electrical Network Analysis Dynamic Optimal Control Policy Forecasting for Supply Chain and Portfolio Management Variational Analysis in Bilevel Programming Game Engineering Games of Connectivity Robust Feedback Nash Equilibrium De Facto Delegation and Proposer Rules Bargaining Set in Effectivity Function Dynamic Oligopoly as a Mixed Large Game -- Toy Market, Balanced Games, Market Equilibrium for Combinatorial Auctions and the Matching Core of Non-negative TU Games Continuity, Manifolds and Arrow's Social Choice Problem Mixture Class of Stochastic Games.

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S. K. Neogy

Papers

On Invex Sets and Preinvex Functions

The generalized linear complementarity problem revisited

More on positive subdefinite matrices and the linear complementarity problem

On the classes of fully copositive and fully semimonotone matrices

Mathematical programming and game theory for decision making