Abstract: Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.
Abstract: Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.
Abstract: In this study, a multi objective optimization for end
milling of Al 6061 alloy has been presented to provide better
surface quality and higher Material Removal Rate (MRR). The input
parameters considered for the analysis are spindle speed, depth of cut
and feed. The experiments were planned as per Taguchis design of
experiment, with L27 orthogonal array. The Grey Relational Analysis
(GRA) has been used for transforming multiple quality responses
into a single response and the weights of the each performance
characteristics are determined by employing the Principal Component
Analysis (PCA), so that their relative importance can be properly and
objectively described. The results reveal that Taguchi based G-PCA
can effectively acquire the optimal combination of cutting parameters.
Abstract: Waste Load Allocation (WLA) strategies usually
intend to find economic policies for water resource management.
Water quality trading (WQT) is an approach that uses discharge
permit market to reduce total environmental protection costs. This
primarily requires assigning discharge limits known as total
maximum daily loads (TMDLs). These are determined by monitoring
organizations with respect to the receiving water quality and
remediation capabilities. The purpose of this study is to compare two
approaches of TMDL assignment for WQT policy in small catchment
area of Haraz River, in north of Iran. At first, TMDLs are assigned
uniformly for the whole point sources to keep the concentrations of
BOD and dissolved oxygen (DO) at the standard level at checkpoint
(terminus point). This was simply simulated and controlled by
Qual2kw software. In the second scenario, TMDLs are assigned
using multi objective particle swarm optimization (MOPSO) method
in which the environmental violation at river basin and total treatment
costs are minimized simultaneously. In both scenarios, the equity
index and the WLA based on trading discharge permits (TDP) are
calculated. The comparative results showed that using economically
optimized TMDLs (2nd scenario) has slightly more cost savings rather
than uniform TMDL approach (1st scenario). The former annually
costs about 1 M$ while the latter is 1.15 M$. WQT can decrease
these annual costs to 0.9 and 1.1 M$, respectively. In other word,
these approaches may save 35 and 45% economically in comparison
with command and control policy. It means that using multi objective
decision support systems (DSS) may find more economical WLA,
however its outcome is not necessarily significant in comparison with
uniform TMDLs. This may be due to the similar impact factors of
dischargers in small catchments. Conversely, using uniform TMDLs
for WQT brings more equity that makes stakeholders not feel that
much envious of difference between TMDL and WQT allocation. In
addition, for this case, determination of TMDLs uniformly would be
much easier for monitoring. Consequently, uniform TMDL for TDP
market is recommended as a sustainable approach. However,
economical TMDLs can be used for larger watersheds.
Abstract: In this paper, the goal programming methodology for
solving multiple objective problem of the technological variants and
production plan optimization has been applied. The optimization
criteria are determined and the multiple objective linear programming
model for solving a problem of the technological variants and
production plan optimization is formed and solved. Then the obtained
results are analysed. The obtained results point out to the possibility
of efficient application of the goal programming methodology in
solving the problem of the technological variants and production plan
optimization. The paper points out on the advantages of the
application of the goal programming methodology compare to the
Surrogat Worth Trade-off method in solving this problem.
Abstract: Assembly line balancing problem is aimed to divide
the tasks among the stations in assembly lines and optimize some
objectives. In assembly lines the workload on stations is different
from each other due to different tasks times and the difference in
workloads between stations can cause blockage or starvation in some
stations in assembly lines. Buffers are used to store the semi-finished
parts between the stations and can help to smooth the assembly
production. The assembly line balancing and buffer sizing problem
can affect the throughput of the assembly lines. Assembly line
balancing and buffer sizing problems have been studied separately in
literature and due to their collective contribution in throughput rate of
assembly lines, balancing and buffer sizing problem are desired to
study simultaneously and therefore they are considered concurrently
in current research. Current research is aimed to maximize
throughput, minimize total size of buffers in assembly line and
minimize workload variations in assembly line simultaneously. A
multi objective optimization objective is designed which can give
better Pareto solutions from the Pareto front and a simple example
problem is solved for assembly line balancing and buffer sizing
simultaneously. Current research is significant for assembly line
balancing research and it can be significant to introduce optimization
approaches which can optimize current multi objective problem in
future.
Abstract: Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.
Abstract: Process planning and production scheduling play
important roles in manufacturing systems. In this paper a multiobjective
mixed integer linear programming model is presented for
the integrated planning and scheduling of multi-product. The aim is
to find a set of high-quality trade-off solutions. This is a
combinatorial optimization problem with substantially large solution
space, suggesting that it is highly difficult to find the best solutions
with the exact search method. To account for it, a PSO-based
algorithm is proposed by fully utilizing the capability of the
exploration search and fast convergence. To fit the continuous PSO
in the discrete modeled problem, a solution representation is used in
the algorithm. The numerical experiments have been performed to
demonstrate the effectiveness of the proposed algorithm.
Abstract: Vehicle suspension design must fulfill
some conflicting criteria. Among those is ride comfort
which is attained by minimizing the acceleration
transmitted to the sprung mass, via suspension spring
and damper. Also good handling of a vehicle is a
desirable property which requires stiff suspension and
therefore is in contrast with a vehicle with good ride.
Among the other desirable features of a suspension is
the minimization of the maximum travel of suspension.
This travel which is called suspension working space in
vehicle dynamics literature is also a design constraint
and it favors good ride. In this research a full car 8
degrees of freedom model has been developed and the
three above mentioned criteria, namely: ride, handling
and working space has been adopted as objective
functions. The Multi Objective Programming (MOP)
discipline has been used to find the Pareto Front and
some reasoning used to chose a design point between
these non dominated points of Pareto Front.
Abstract: Scheduling for the flexible job shop is very important
in both fields of production management and combinatorial
optimization. However, it quit difficult to achieve an optimal solution
to this problem with traditional optimization approaches owing to the
high computational complexity. The combining of several
optimization criteria induces additional complexity and new
problems. In this paper, a Pareto approach to solve the multi
objective flexible job shop scheduling problems is proposed. The
objectives considered are to minimize the overall completion time
(makespan) and total weighted tardiness (TWT). An effective
simulated annealing algorithm based on the proposed approach is
presented to solve multi objective flexible job shop scheduling
problem. An external memory of non-dominated solutions is
considered to save and update the non-dominated solutions during
the solution process. Numerical examples are used to evaluate and
study the performance of the proposed algorithm. The proposed
algorithm can be applied easily in real factory conditions and for
large size problems. It should thus be useful to both practitioners and
researchers.
Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: This paper aims to develop a model that assists the
international retailer in selecting the country that maximizes the
degree of fit between the retailer-s goals and the country
characteristics in his initial internationalization move. A two-stage
multi criteria decision model is designed integrating the Analytic
Hierarchy Process (AHP) and Goal Programming. Ethical, cultural,
geographic and economic proximity are identified as the relevant
constructs of the internationalization decision. The constructs are
further structured into sub-factors within analytic hierarchy. The
model helps the retailer to integrate, rank and weigh a number of
hard and soft factors and prioritize the countries accordingly. The
model has been implemented on a Turkish luxury goods retailer who
was planning to internationalize. Actual entry of the specific retailer
in the selected country is a support for the model. Implementation on
a single retailer limits the generalizability of the results; however, the
emphasis of the paper is on construct identification and model
development. The paper enriches the existing literature by proposing
a hybrid multi objective decision model which introduces new soft
dimensions i.e. perceived distance, ethical proximity, humane
orientation to the decision process and facilitates effective decision
making.
Abstract: Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
Abstract: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
Abstract: The weight constrained shortest path problem
(WCSPP) is one of most several known basic problems in
combinatorial optimization. Because of its importance in many areas
of applications such as computer science, engineering and operations
research, many researchers have extensively studied the WCSPP.
This paper mainly concentrates on the reduction of total search space
for finding WCSP using some existing Genetic Algorithm (GA). For
this purpose, some controlled schemes of genetic operators are
adopted on list chromosome representation. This approach gives a
near optimum solution with smaller elapsed generation than classical
GA technique. From further analysis on the matter, a new
generalized schema theorem is also developed from the philosophy
of Holland-s theorem.
Abstract: Several approaches such as linear programming, network
modeling, greedy heuristic and decision support system are well-known
approaches in solving irregular airline operation problem. This paper
presents an alternative approach based on Multi Objective Micro Genetic
Algorithm. The aim of this research is to introduce the concept of Multi
Objective Micro Genetic Algorithm as a tool to solve irregular airline
operation, combine and reroute problem. The experiment result indicated
that the model could obtain optimal solutions within a few second.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.