Multiobjective optimal power plant operation requires an optimal mapping between unit load demand and pressure set-point in a Fossil Fuel Power Unit (FFPU). In general, the optimization problem with varying unit load demand cannot be solved using a fixed nonlinear mapping. This paper presents a modern heuristic method, Particle Swarm Optimization (PSO), to realize the optimal mapping by searchi...

With the popularity of different power generators in an electric micro-grid system, their operation scheduling as the load demand changes becomes an important task. Besides satisfying load balance constraint and generator’s rated power, several other practicalities, such a limited use of grid power and restricted ramping of power output from generators, arise and must be considered during the o...

This paper presented a mixed integer programming for integrated scheduling and process planning. The presented process plan included some orders with precedence relations similar to Multiple Traveling Salesman Problem (MTSP), which was categorized as an NP-hard problem. These types of problems are also called advanced planning because of simultaneously determining the appropriate sequence and m...

Different methods are available for simultaneous optimization of cross-section, topology and geometry of truss structures. Since the search space for this problem is very large, the probability of falling in local optimum is considerably high. On the other hand, different types of design variables (continuous and discrete) lead to some difficulties in the process of optimization. In this articl...

In this work we focus on the energy efficiency challenge in wireless sensor networks, from both an on-line perspective (related to routing), as well as a network design perspective (related to tracking). We investigate a few representative, important aspects of energy efficiency: a) the robust and fast data propagation b) the problem of balancing the energy dissipation among all sensors in the ...

In this paper we show how the classical job shop scheduling problem can be modeled as a special class of acyclic timed automata Finding an optimal schedule corresponds then to nding a shortest in terms of elapsed time path in the timed automaton This representa tion provides new techniques for solving the optimization problem and more importantly it allows to model naturally more complex dynami...

In this paper we deal with the problem of building new or extending an existing railway infrastructure. The goal is to determine a minimum cost infrastructure fulfilling the requirements defined by an integrated timetable and the operation of the railway system. We first model this planning task as a combinatorial network optimization problem, capturing the essential aspects. We then present a ...

In this paper, we consider the problem of generating optimized, executable control code from high-level, symbolic specifications. In particular, we construct symbolic control programs using strings from a motion description language with a nominal set of motion parameters, such as temporal duration and energy, embedded within each mode. These parameters are then optimized over, using tools from...

Many real world problems can be modelled as an optimization problem. Evolutionary algorithms are used to solve these problems. Ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. These ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. Ant colony optim...