State intervention inevitably fails due to the inherent flaws as highlighted by Austrian political economy. Interventionism distorts prices, disrupts the competitive discovery process, and is socially harmful. Disintervention is posed as a solution, yet typical disintervention is often a centrally planned solution to the problems inherent to central planning. In many ways intervention and disin...

this paper presents an application of benders decomposition to deal with the complexities in the simultaneous generation expansion planning (gep) and transmission expansion planning (tep). unlike the power system operation fields of study, the power system planning methods are not expected to be fast. however, it is always preferable to speed up computations to provide more analysis options for...

In recent years, significant research efforts have been devoted to the optimal planning of power systems. Substation Expansion Planning (SEP) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future load demand. The large number of design variables and combination of discr...

this paper presents optimal control method to path planning of mobile robots with flexible joints. dynamic equations are derived and additional kinematic constraints are used to solve the extra dofs arose from base mobility. then with modeling the elasticity at each joint as a linear torsinal spring, the set of equations are formed. the hamiltonian function is formed and the necessary condition...

In CPP, we are given a set of actions (assumed deterministic in this paper), a distribution over initial states, a goal condition, and a real value 0 < θ ≤ 1. We seek a plan π such that following its execution, the goal probability is at least θ. Motivated by the success of the translation-based approach for conformant planning, introduced by Palacios and Geffner, we suggest a new compilation s...

ion Heuristics An abstraction of a planning domain Σ is a γ-preserving homomorphism from Σ onto a smaller planning domain Σ′. For each planning problem P = (Σ, s0, g), this defines a corresponding abstraction P ′ = (Σ′, s0, g ′); and if we let c∗ denote the cost of an optimal solution to a planning problem, then it follows that c∗(P ′) ≤ c∗(P ). If Σ′ is simple enough that we can compute c∗(P ′...

Distributed case-based reasoning architectures have the potential to improve the overall performance of case-based reasoning systems. In this paper we describe a collaborative case-based reasoning architecture, which allows problem solving experiences to be shared among multiple agents. We demonstrate how this technique can be used successfully to solve an important challenge in the area of per...