A new Meta heuristic approach called ”Randomized gravitational emulation search algorithm (RGES)” for solving large size set covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters ’velocity’ and ’gravity’ in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility ...

recently, much attention has been given to stochastic demand due to uncertainty in the real -world. in the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. on the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. the supplier selection pl...

An efficient assignment and scheduling of tasks is one of the key elements in effective utilization of heterogeneous multiprocessor systems. The task scheduling problem has been proven to be NP-hard is the reason why we used meta-heuristic (guided-random-search-based) methods for finding a suboptimal schedule. Due to the large solution space that a meta-heuristic algorithm is required to cover,...

The main aim of this chapter is to present and discuss a set of modeling and specification techniques, in what concerns their ontology and support in the requirements representation of computer-based systems. A systematic classification of meta-models, also called models of computation, is presented. This topic is highly relevant since it supports the definition of sound specification methodolo...

This work deals with memetic-computing agent-models based on the cooperative integration of search agents endowed with (possibly different) optimization strategies, in particular memetic algorithms. As a proof-ofconcept of the model, we deploy it on the tool switching problem (ToSP), a hard combinatorial optimization problem that arises in the area of flexible manufacturing. The ToSP has been t...

In this research application paper, the usefulness of an intelligent mechanism (a cubic spline smoothing technique) for determining when to switch from one algorithm to another within a meta heuristic search process is explored. We concentrated on a typical planning problem for a southern United States forestry company where the net present value of management activities is maximized subject to...

Meta-heuristics are algorithms which are applied to solve problems when conventional algorithms can not find good solutions in reasonable time; evolutionary algorithms are perhaps the most well-known examples of meta-heuristics. As there are many possible meta-heuristics, finding the most suitable meta-heuristic for a given problem is not a trivial task. In order to make this choice, one can de...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...

this paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzz...