Inverse optimisation and linear programming have emerged as crucial instruments in addressing complex decision-making problems where underlying models must be inferred from observed behaviour. At its ...

Estimation errors or uncertainities in expected return and risk measures create difficulties for portfolio optimization. The literature deals with the uncertainty using stochastic, fuzzy or ...

This example shows how to use PROC LP to solve a linear goal-programming problem. PROC LP has the ability to solve a series of linear programs, each with a new objective function. These objective ...

Model abstraction for finite state automata is helpful for decreasing computational complexity and improving comprehensibility for the verification and control synthesis of discrete-event systems (DES ...

The optimisation of gas networks has emerged as a critical field in energy systems engineering, incorporating advanced nonlinear programming techniques to address the increasing complexity of gas ...