Abstract: Bezier curves have useful properties for path
generation problem, for instance, it can generate the reference
trajectory for vehicles to satisfy the path constraints. Both algorithms
join cubic Bezier curve segment smoothly to generate the path. Some
of the useful properties of Bezier are curvature. In mathematics,
curvature is the amount by which a geometric object deviates from
being flat, or straight in the case of a line. Another extrinsic example
of curvature is a circle, where the curvature is equal to the reciprocal
of its radius at any point on the circle. The smaller the radius, the
higher the curvature thus the vehicle needs to bend sharply. In this
study, we use Bezier curve to fit highway-like curve. We use
different approach to find the best approximation for the curve so that
it will resembles highway-like curve. We compute curvature value by
analytical differentiation of the Bezier Curve. We will then compute
the maximum speed for driving using the curvature information
obtained. Our research works on some assumptions; first, the Bezier
curve estimates the real shape of the curve which can be verified
visually. Even though, fitting process of Bezier curve does not
interpolate exactly on the curve of interest, we believe that the
estimation of speed are acceptable. We verified our result with the
manual calculation of the curvature from the map.
Abstract: Concurrent planning of project scheduling and
material ordering has been increasingly addressed within last decades
as an approach to improve the project execution costs. Therefore, we
have taken the problem into consideration in this paper, aiming to
maximize schedules quality robustness, in addition to minimize the
relevant costs. In this regard, a bi-objective mathematical model is
developed to formulate the problem. Moreover, it is possible to
utilize the all-unit discount for materials purchasing. The problem is
then solved by the E-constraint method, and the Pareto front is
obtained for a variety of robustness values. The applicability and
efficiency of the proposed model is tested by different numerical
instances, finally.
Abstract: Finding the optimal 3D path of an aerial vehicle under
flight mechanics constraints is a major challenge, especially when
the algorithm has to produce real time results in flight. Kinematics
models and Pythagorian Hodograph curves have been widely used
in mobile robotics to solve this problematic. The level of difficulty
is mainly driven by the number of constraints to be saturated at the
same time while minimizing the total length of the path. In this paper,
we suggest a pragmatic algorithm capable of saturating at the same
time most of dimensioning helicopter 3D trajectories’ constraints
like: curvature, curvature derivative, torsion, torsion derivative, climb
angle, climb angle derivative, positions. The trajectories generation
algorithm is able to generate versatile complex 3D motion primitives
feasible by a helicopter with parameterization of the curvature and the
climb angle. An upper ”motion primitives’ concatenation” algorithm
is presented based. In this article we introduce a new way of designing
three-dimensional trajectories based on what we call the ”Dubins
gliding symmetry conjecture”. This extremely performing algorithm
will be soon integrated to a real-time decisional system dealing with
inflight safety issues.
Abstract: The agenda of showing the scheduled time for
performing certain tasks is known as timetabling. It is widely used in
many departments such as transportation, education, and production.
Some difficulties arise to ensure all tasks happen in the time and
place allocated. Therefore, many researchers invented various
programming models to solve the scheduling problems from several
fields. However, the studies in developing the general integer
programming model for many timetabling problems are still
questionable. Meanwhile, this thesis describes about creating a
general model which solves different types of timetabling problems
by considering the basic constraints. Initially, the common basic
constraints from five different fields are selected and analyzed. A
general basic integer programming model was created and then
verified by using the medium set of data obtained randomly which is
much similar to realistic data. The mathematical software, AIMMS
with CPLEX as a solver has been used to solve the model. The model
obtained is significant in solving many timetabling problems easily
since it is modifiable to all types of scheduling problems which have
same basic constraints.
Abstract: Countryside has been generally recognized and
regarded as a characteristic symbol which presents in human memory
for a long time. As a result of the change of times, because of it is
failure to meet the growing needs of the growing life and mental
decline, the vast rural area began to decline. But their history feature
image which accumulated by the ancient tradition provides people
with the origins of existence on the spiritual level, such as "identity"
and "belonging", makes people closer to the others in the spiritual and
psychological aspects of a common experience about the past, thus the
sense of a lack of culture caused by the losing of memory symbols is
weakened. So, in the modernization process, how to repair its vitality
and transform and planning it in a sustainable way has become a hot
topics in architectural and urban planning. This paper aims to break
the constraints of disciplines, from the perspective of interdiscipline,
using the research methods of systems science to analyze and discuss
the theories and methods of rural form factors, which based on the
viewpoint of memory in psychology. So we can find a right way to
transform the Rural to give full play to the role of the countryside in
the actual use and the shape of history spirits.
Abstract: Manufacturing tolerancing is intended to determine
the intermediate geometrical and dimensional states of the part during
its manufacturing process. These manufacturing dimensions also
serve to satisfy not only the functional requirements given in the
definition drawing, but also the manufacturing constraints, for
example geometrical defects of the machine, vibration and the wear
of the cutting tool. The choice of positioning has an important influence on the cost
and quality of manufacture. To avoid this problem, a two-step
approach has been developed. The first step is dedicated to the
determination of the optimum position. As for the second step, a
study was carried out for the tightening effect on the tolerance
interval.
Abstract: The paper shows that on transferring sense from the
SL to the TL, the translator’s reading against the grain determines the
creation of a faulty pattern of rendering the original meaning in the
receiving culture which reflects the use of misleading transformative
codes. In this case, the translator is a writer per se who decides what
goes in and out of the book, how the style is to be ciphered and what
elements of ideology are to be highlighted. The paper also proves that
figurative language must not be flattened for the sake of clarity or
naturalness. The missing figurative elements make the translated text
less interesting, less challenging and less vivid which reflects poorly
on the writer. There is a close connection between style and the
writer’s person. If the writer’s style is very much altered in a
translation, the translation is useless as the original writer and his /
her imaginative world can no longer be discovered. The purpose of the paper is to prove that adaptation is a dangerous
tool which leads to variants that sometimes reflect the original less
than the reader would wish to. It contradicts the very essence of the
process of translation which is that of making an original work
available in a foreign language. If the adaptive transformative codes
are so flexible that they encourage the translator to repeatedly leave
out parts of the original work, then a subversive pattern emerges
which changes the entire book. In conclusion, as a result of using adaptation, manipulative or
subversive effects are created in the translated work. This is generally
achieved by adding new words or connotations, creating new figures
of speech or using explicitations. The additional meanings of the
original work are neglected and the translator creates new meanings,
implications, emphases and contexts. Again s/he turns into a new
author who enjoys the freedom of expressing his / her own ideas
without the constraints of the original text. Reading against the grain
is unadvisable during the process of translation and consequently,
following personal common sense becomes essential in the field of
translation as well as everywhere else, so that translation should not
become a source of fantasy.
Abstract: This paper evaluates the accrual based scheduling for
cloud in single and multi-resource system. Numerous organizations
benefit from Cloud computing by hosting their applications. The
cloud model provides needed access to computing with potentially
unlimited resources. Scheduling is tasks and resources mapping to a
certain optimal goal principle. Scheduling, schedules tasks to virtual
machines in accordance with adaptable time, in sequence under
transaction logic constraints. A good scheduling algorithm improves
CPU use, turnaround time, and throughput. In this paper, three realtime
cloud services scheduling algorithm for single resources and
multiple resources are investigated. Experimental results show
Resource matching algorithm performance to be superior for both
single and multi-resource scheduling when compared to benefit first
scheduling, Migration, Checkpoint algorithms.
Abstract: In recent years, new techniques for solving complex
problems in engineering are proposed. One of these techniques is
JPSO algorithm. With innovative changes in the nature of the jump
algorithm JPSO, it is possible to construct a graph-based solution
with a new algorithm called G-JPSO. In this paper, a new algorithm
to solve the optimal control problem Fletcher-Powell and optimal
control of pumps in water distribution network was evaluated.
Optimal control of pumps comprise of optimum timetable operation
(status on and off) for each of the pumps at the desired time interval.
Maximum number of status on and off for each pumps imposed to the
objective function as another constraint. To determine the optimal
operation of pumps, a model-based optimization-simulation
algorithm was developed based on G-JPSO and JPSO algorithms.
The proposed algorithm results were compared well with the ant
colony algorithm, genetic and JPSO results. This shows the
robustness of proposed algorithm in finding near optimum solutions
with reasonable computational cost.
Abstract: This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.
Abstract: This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.
Abstract: For a rigid body sliding on a rough surface, a range of
uncertainty or non-uniqueness of solution could be found, which is
termed: Painlevé paradox. Painlevé paradox is the reason of a wide
range of bouncing motion, observed during sliding of robotic
manipulators on rough surfaces. In this research work, the existence
of the paradox zone during the sliding motion of a two-link (P-R)
robotic manipulator with a unilateral constraint is investigated.
Parametric study is performed to investigate the effect of friction,
link-length ratio, total height and link-mass ratio on the paradox zone.
Abstract: This paper considers the design of Dual Proportional-
Integral (DPI) Load Frequency Control (LFC), using gravitational
search algorithm (GSA). The design is carried out for nonlinear
hydrothermal power system where generation rate constraint (GRC)
and governor dead band are considered. Furthermore, time delays
imposed by governor-turbine, thermodynamic process, and
communication channels are investigated. GSA is utilized to search
for optimal controller parameters by minimizing a time-domain based
objective function. GSA-based DPI has been compared to Ziegler-
Nichols based PI, and Genetic Algorithm (GA) based PI controllers
in order to demonstrate the superior efficiency of the proposed
design. Simulation results are carried for a wide range of operating
conditions and system parameters variations.
Abstract: This study presents a hybrid metaheuristic algorithm
to obtain optimum designs for steel space buildings. The optimum
design problem of three-dimensional steel frames is mathematically
formulated according to provisions of LRFD-AISC (Load and
Resistance factor design of American Institute of Steel Construction).
Design constraints such as the strength requirements of structural
members, the displacement limitations, the inter-story drift and the
other structural constraints are derived from LRFD-AISC
specification. In this study, a hybrid algorithm by using teachinglearning
based optimization (TLBO) and harmony search (HS)
algorithms is employed to solve the stated optimum design problem.
These algorithms are two of the recent additions to metaheuristic
techniques of numerical optimization and have been an efficient tool
for solving discrete programming problems. Using these two
algorithms in collaboration creates a more powerful tool and
mitigates each other’s weaknesses. To demonstrate the powerful
performance of presented hybrid algorithm, the optimum design of a
large scale steel building is presented and the results are compared to
the previously obtained results available in the literature.
Abstract: In recent decades, probabilistic constrained optimal
control problems have attracted much attention in many research
fields. Although probabilistic constraints are generally intractable
in an optimization problem, several tractable methods haven been
proposed to handle probabilistic constraints. In most methods,
probabilistic constraints are reduced to deterministic constraints
that are tractable in an optimization problem. However, there is a
gap between the transformed deterministic constraints in case of
known and unknown probability distribution. This paper examines
the conservativeness of probabilistic constrained optimization method
for unknown probability distribution. The objective of this paper is
to provide a quantitative assessment of the conservatism for tractable
constraints in probabilistic constrained optimization with unknown
probability distribution.
Abstract: In the present paper the design of plate heat exchangers
is formulated as an optimization problem considering two
mathematical modelling. The number of plates is the objective
function to be minimized, considering implicitly some parameters
configuration. Screening is the optimization method used to solve the
problem. Thermal and hydraulic constraints are verified, not viable
solutions are discarded and the method searches for the convergence to
the optimum, case it exists. A case study is presented to test the
applicability of the developed algorithm. Results show coherency with
the literature.
Abstract: Land reallocation is one of the most important steps in
land consolidation projects. Many different models were proposed for
land reallocation in the literature such as Fuzzy Logic, block priority
based land reallocation and Spatial Decision Support Systems. A
model including four parts is considered for automatic block
reallocation with genetic algorithm method in land consolidation
projects. These stages are preparing data tables for a project land,
determining conditions and constraints of land reallocation, designing
command steps and logical flow chart of reallocation algorithm and
finally writing program codes of Genetic Algorithm respectively. In
this study, we designed the first three steps of the considered model
comprising four steps.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: Work presented is interested in the characterization of
the quasistatic mechanical properties and in fatigue of a composite
laminated in jute/epoxy. The natural fibers offer promising prospects
thanks to their interesting specific properties, because of their low
density, but also with their bio-deterioration. Several scientific
studies highlighted the good mechanical resistance of the vegetable
fiber composites reinforced, even after several recycling. Because of
the environmental standards that become increasingly severe, one
attends the emergence of eco-materials at the base of natural fibers
such as flax, bamboo, hemp, sisal, jute. The fatigue tests on
elementary vegetable fibers show an increase of about 60% of the
rigidity of elementary fibers of hemp subjected to cyclic loadings. In
this study, the test-tubes manufactured by the method infusion have
sequences of stacking of 0/90° and ± 45° for the shearing and tensile
tests. The quasistatic tests reveal a variability of the mechanical
properties of about 8%. The tensile fatigue tests were carried out for
levels of constraints equivalent to half of the ultimate values of the
composite. Once the fatigue tests carried out for well-defined values
of cycles, a series of static tests of traction type highlights the
influence of the number of cycles on the quasi-static mechanical
behavior of the laminate jute/epoxy.
Abstract: In this article, we deal with a variant of the classical
course timetabling problem that has a practical application in many
areas of education. In particular, in this paper we are interested in
high schools remedial courses. The purpose of such courses is to
provide under-prepared students with the skills necessary to succeed
in their studies. In particular, a student might be under prepared in
an entire course, or only in a part of it. The limited availability
of funds, as well as the limited amount of time and teachers at
disposal, often requires schools to choose which courses and/or which
teaching units to activate. Thus, schools need to model the training
offer and the related timetabling, with the goal of ensuring the
highest possible teaching quality, by meeting the above-mentioned
financial, time and resources constraints. Moreover, there are some
prerequisites between the teaching units that must be satisfied. We
first present a Mixed-Integer Programming (MIP) model to solve
this problem to optimality. However, the presence of many peculiar
constraints contributes inevitably in increasing the complexity of
the mathematical model. Thus, solving it through a general-purpose
solver may be performed for small instances only, while solving
real-life-sized instances of such model requires specific techniques
or heuristic approaches. For this purpose, we also propose a heuristic
approach, in which we make use of a fast constructive procedure
to obtain a feasible solution. To assess our exact and heuristic
approaches we perform extensive computational results on both
real-life instances (obtained from a high school in Lecce, Italy) and
randomly generated instances. Our tests show that the MIP model is
never solved to optimality, with an average optimality gap of 57%.
On the other hand, the heuristic algorithm is much faster (in about the
50% of the considered instances it converges in approximately half of
the time limit) and in many cases allows achieving an improvement
on the objective function value obtained by the MIP model. Such an
improvement ranges between 18% and 66%.