Real life phenomena are often modelled by ordinary/partial differential equations. Due to the local nature of
ordinary differential operator(ODO), the models containing
merely ODOs do not help in modelling memory and hereditary properties. One of the best remedies to overcome
this drawback is the introduction of integral term in the
model. The ordinary/partial differential equation along with
the weighted integral of unknown function gives rise to an
integro-differential equation (IDE) or a partial integro-differential equation (PIDE) respectively. Analysis of
such equations can be found in[1-4].
Applications of PIDEs can be found in various fields.
Dehghan and shakeri[5] have used variational iteration
method (VIM) to solve PIDEs arising in heat conduction of
materials with memory. Various numerical schemes are
proposed by Dehghan[6] to solve PIDEs arising in viscoelasticity. Nonlinear PIDEs arising in nuclear reactor dynamics are solved by Pao[7] and Pachapatte[8]. PIDEs have
been used in jump-diffusion models for pricing of derivatives in finance[9]. Abergel[10] used a nonlinear PIDE in
financial modelling. Hepperger[11] proposed a PIDE in the
model of electricity swaptions. A PIDE governing biofluid
flow in fractured biomaterials is proposed by Zadeh in[12].
The most promising tool for solving linear equations is
the Laplace transform (LT) method[13,14]. LT is used in[16]
for calculations of water flow and heat transfer in fractured
rocks. Alquran et al.[17] used LT to solve non
-homogeneous partial differential equations. Merdan et al.
* Corresponding author:
sachin.math@yahoo.co.in (Sachin Bhalekar)
Published online at http://journal.sapub.org/ajcam
Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved
[18] proposed a new method for nonlinear oscillatory systems using LT.
Stiff systems of ODEs are solved by Aminikhah[19] using a combined LT and HPM. Kexue and Jiger[20] have
utilized LT to solve problems arising in fractional differential equations.
In this article we propose a most general form of a linear
PIDE in two independent variables with a convolution kernel. In Section 2 we provide some preliminaries regarding
LT. Section 3 is devoted to the proposed method and Section 4 provides an ample number of examples of various
types.