Abstract: This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Abstract: Mathematical programming has been applied to various
problems. For many actual problems, the assumption that the parameters
involved are deterministic known data is often unjustified. In
such cases, these data contain uncertainty and are thus represented
as random variables, since they represent information about the
future. Decision-making under uncertainty involves potential risk.
Stochastic programming is a commonly used method for optimization
under uncertainty. A stochastic programming problem with recourse
is referred to as a two-stage stochastic problem. In this study, we
consider a stochastic programming problem with simple integer
recourse in which the value of the recourse variable is restricted to a
multiple of a nonnegative integer. The algorithm of a dynamic slope
scaling procedure for solving this problem is developed by using a
property of the expected recourse function. Numerical experiments
demonstrate that the proposed algorithm is quite efficient. The
stochastic programming model defined in this paper is quite useful
for a variety of design and operational problems.
Abstract: Let k, t, d be arbitrary integers with k ≥ 2, t ≥ 0 and
d = k2 - k. In the first section we give some preliminaries from
Pell equations x2 - dy2 = 1 and x2 - dy2 = N, where N be any
fixed positive integer. In the second section, we consider the integer
solutions of Pell equations x2 - dy2 = 1 and x2 - dy2 = 2t. We
give a method for the solutions of these equations. Further we derive
recurrence relations on the solutions of these equations
Abstract: For positive integer s and t, the Ramsey number R(s, t)
is the least positive integer n such that for every graph G of order n, either G contains Ks as a subgraph or G contains Kt as a subgraph.
We construct the circulant graphs and use them to obtain lower bounds of some small Ramsey numbers.
Abstract: This paper presents a integer frequency offset (IFO)
estimation scheme for the 3GPP long term evolution (LTE) downlink
system. Firstly, the conventional joint detection method for IFO and
sector cell index (CID) information is introduced. Secondly, an IFO
estimation without explicit sector CID information is proposed, which
can operate jointly with the proposed IFO estimation and reduce
the time delay in comparison with the conventional joint method.
Also, the proposed method is computationally efficient and has almost
similar performance in comparison with the conventional method over
the Pedestrian and Vehicular channel models.
Abstract: In this work, we consider the number of integer solutions
of Diophantine equation D : y2 - 2yx - 3 = 0 over Z and
also over finite fields Fp for primes p ≥ 5. Later we determine the
number of rational points on curves Ep : y2 = Pp(x) = yp
1 + yp
2
over Fp, where y1 and y2 are the roots of D. Also we give a formula
for the sum of x- and y-coordinates of all rational points (x, y) on
Ep over Fp.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.
Abstract: Rapid economic development and population growth
in Malaysia had accelerated the generation of solid waste. This issue
gives pressure for effective management of municipal solid waste
(MSW) to take place in Malaysia due to the increased cost of landfill.
This paper discusses optimal planning of waste-to-energy (WTE)
using a combinatorial simulation and optimization model through
mixed integer linear programming (MILP) approach. The proposed
multi-period model is tested in Iskandar Malaysia (IM) as case study
for a period of 12 years (2011 -2025) to illustrate the economic
potential and tradeoffs involved in this study. In this paper, 3
scenarios have been used to demonstrate the applicability of the
model: (1) Incineration scenario (2) Landfill scenario (3) Optimal
scenario. The model revealed that the minimum cost of electricity
generation from 9,995,855 tonnes of MSW is estimated as USD
387million with a total electricity generation of 50MW /yr in the
optimal scenario.
Abstract: We address the balancing problem of transfer lines in
this paper to find the optimal line balancing that minimizes the nonproductive
time. We focus on the tool change time and face
orientation change time both of which influence the makespane. We
consider machine capacity limitations and technological constraints
associated with the manufacturing process of auto cylinder heads.
The problem is represented by a mixed integer programming model
that aims at distributing the design features to workstations and
sequencing the machining processes at a minimum non-productive
time. The proposed model is solved by an algorithm established using
linearization schemes and Benders- decomposition approach. The
experiments show the efficiency of the algorithm in reaching the
exact solution of small and medium problem instances at reasonable
time.
Abstract: As the air traffic increases at a hub airport, some
flights cannot land or depart at their preferred target time. This event
happens because the airport runways become occupied to near their
capacity. It results in extra costs for both passengers and airlines
because of the loss of connecting flights or more waiting, more fuel
consumption, rescheduling crew members, etc. Hence, devising an
appropriate scheduling method that determines a suitable runway and
time for each flight in order to efficiently use the hub capacity and
minimize the related costs is of great importance. In this paper, we
present a mixed-integer zero-one model for scheduling a set of mixed
landing and departing flights (despite of most previous studies
considered only landings). According to the fact that the flight cost is
strongly affected by the level of airline, we consider different airline
categories in our model. This model presents a single objective
minimizing the total sum of three terms, namely 1) the weighted
deviation from targets, 2) the scheduled time of the last flight (i.e.,
makespan), and 3) the unbalancing the workload on runways. We
solve 10 simulated instances of different sizes up to 30 flights and 4
runways. Optimal solutions are obtained in a reasonable time, which
are satisfactory in comparison with the traditional rule, namely First-
Come-First-Serve (FCFS) that is far apart from optimality in most
cases.
Abstract: Fractional-order controller was proven to perform better than the integer-order controller. However, the absence of a pole at origin produced marginal error in fractional-order control system. This study demonstrated the enhancement of the fractionalorder PI over the integer-order PI in a steam temperature control. The fractional-order controller was cascaded with an error compensator comprised of a very small zero and a pole at origin to produce a zero steady-state error for the closed-loop system. Some modification on the error compensator was suggested for different order fractional integrator that can improve the overall phase margin.
Abstract: The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.
Abstract: Let p be a prime number, Fp be a finite field and t ∈ F*p= Fp- {0}. In this paper we obtain some properties of ellipticcurves Ep,t: y2= y2= x3- t2x over Fp. In the first sectionwe give some notations and preliminaries from elliptic curves. In the second section we consider the rational points (x, y) on Ep,t. Wegive a formula for the number of rational points on Ep,t over Fnp for an integer n ≥ 1. We also give some formulas for the sum of x?andy?coordinates of the points (x, y) on Ep,t. In the third section weconsider the rank of Et: y2= x3- t2x and its 2-isogenous curve Et over Q. We proved that the rank of Etand Etis 2 over Q. In the last section we obtain some formulas for the sums Σt∈F?panp,t for an integer n ≥ 1, where ap,t denote the trace of Frobenius.
Abstract: Ren et al. presented an efficient carrier frequency offset
(CFO) estimation method for orthogonal frequency division multiplexing
(OFDM), which has an estimation range as large as the
bandwidth of the OFDM signal and achieves high accuracy without
any constraint on the structure of the training sequence. However,
its detection probability of the integer frequency offset (IFO) rapidly
varies according to the fractional frequency offset (FFO) change. In
this paper, we first analyze the Ren-s method and define two criteria
suitable for detection of IFO. Then, we propose a novel method for
the IFO estimation based on the maximum-likelihood (ML) principle
and the detection criteria defined in this paper. The simulation results
demonstrate that the proposed method outperforms the Ren-s method
in terms of the IFO detection probability irrespective of a value of
the FFO.
Abstract: This paper is introduced a modification to Diffie-
Hellman protocol to be applicable on the decimal numbers, which
they are the numbers between zero and one. For this purpose we
extend the theory of the congruence. The new congruence is over
the set of the real numbers and it is called the “real congruence"
or the “real modulus". We will refer to the existing congruence by
the “integer congruence" or the “integer modulus". This extension
will define new terms and redefine the existing terms. As the
properties and the theorems of the integer modulus are extended as
well. Modified Diffie-Hellman key exchange protocol is produced a
sharing, secure and decimal secret key for the the cryptosystems that
depend on decimal numbers.
Abstract: Prime Factorization based on Quantum approach in
two phases has been performed. The first phase has been achieved at
Quantum computer and the second phase has been achieved at the
classic computer (Post Processing). At the second phase the goal is to
estimate the period r of equation xrN ≡ 1 and to find the prime factors
of the composite integer N in classic computer. In this paper we
present a method based on Randomized Approach for estimation the
period r with a satisfactory probability and the composite integer N
will be factorized therefore with the Randomized Approach even the
gesture of the period is not exactly the real period at least we can find
one of the prime factors of composite N. Finally we present some
important points for designing an Emulator for Quantum Computer
Simulation.
Abstract: In this paper, a new efficient method for load balancing in low voltage distribution systems is presented. The proposed method introduces an improved Leap-frog method for optimization. The proposed objective function includes the difference between three phase currents, as well as two other terms to provide the integer property of the variables; where the latter are the status of the connection of loads to different phases. Afterwards, a new algorithm is supplemented to undertake the integer values for the load connection status. Finally, the method is applied to different parts of Tabriz low voltage network, where the results have shown the good performance of the proposed method.
Abstract: The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.
Abstract: This study considers the problem of determining
operation and maintenance schedules for a containership equipped
with components during its sailing according to a pre-determined
navigation schedule. The operation schedule, which specifies work
time of each component, determines the due-date of each maintenance
activity, and the maintenance schedule specifies the actual start
time of each maintenance activity. The main constraints are component
requirements, workforce availability, working time limitation,
and inter-maintenance time. To represent the problem mathematically,
a mixed integer programming model is developed. Then,
due to the problem complexity, we suggest a heuristic for the objective
of minimizing the sum of earliness and tardiness between the
due-date and the starting time of each maintenance activity. Computational
experiments were done on various test instances and the
results are reported.
Abstract: In this paper, all variables are supposed to be integer
and positive. In this modern method, objective function is assumed to
be maximized or minimized but constraints are always explained like
less or equal to. In this method, choosing a dual combination of ideal
nonequivalent and omitting one of variables. With continuing this
act, finally, having one nonequivalent with (n-m+1) unknown
quantities in which final nonequivalent, m is counter for constraints,
n is counter for variables of decision.