Abstract: In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.
Abstract: Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.
Abstract: The presence of chemical bonding between functionalized carbon nanotubes and matrix in carbon nanotube reinforced composites is modeled by elastic beam elements representing covalent bonding characteristics. Neglecting other reinforcing mechanisms in the composite such as relatively weak interatomic Van der Waals forces, this model shows close results to the Rule of Mixtures model-s prediction for effective Young-s modulus of a Representative Volume Element of composite for small volume fractions (~1%) and high aspect ratios (L/D>200) of CNTs.
Abstract: An effort has been taken to simulate the combustion
and performance characteristics of biodiesel fuel in direct injection
(D.I) low heat rejection (LHR) diesel engine. Comprehensive
analyses on combustion characteristics such as cylinder pressure,
peak cylinder pressure, heat release and performance characteristics
such as specific fuel consumption and brake thermal efficiency are
carried out. Compression ignition (C.I) engine cycle simulation was
developed and modified in to LHR engine for both diesel and
biodiesel fuel. On the basis of first law of thermodynamics the
properties at each degree crank angle was calculated. Preparation and
reaction rate model was used to calculate the instantaneous heat
release rate. A gas-wall heat transfer calculations are based on the
ANNAND-s combined heat transfer model with instantaneous wall
temperature to analyze the effect of coating on heat transfer. The
simulated results are validated by conducting the experiments on the
test engine under identical operating condition on a turbocharged D.I
diesel engine. In this analysis 20% of biodiesel (derived from
Jatropha oil) blended with diesel and used in both conventional and
LHR engine. The simulated combustion and performance
characteristics results are found satisfactory with the experimental
value.
Abstract: The fundamental aim of extended expansion concept is
to achieve higher work done which in turn leads to higher thermal
efficiency. This concept is compatible with the application of
turbocharger and LHR engine. The Low Heat Rejection engine was
developed by coating the piston crown, cylinder head inside with
valves and cylinder liner with partially stabilized zirconia coating of
0.5 mm thickness. Extended expansion in diesel engines is termed as
Miller cycle in which the expansion ratio is increased by reducing the
compression ratio by modifying the inlet cam for late inlet valve
closing. The specific fuel consumption reduces to an appreciable level
and the thermal efficiency of the extended expansion turbocharged
LHR engine is improved.
In this work, a thermodynamic model was formulated and
developed to simulate the LHR based extended expansion
turbocharged direct injection diesel engine. It includes a gas flow
model, a heat transfer model, and a two zone combustion model. Gas
exchange model is modified by incorporating the Miller cycle, by
delaying inlet valve closing timing which had resulted in considerable
improvement in thermal efficiency of turbocharged LHR engines. The
heat transfer model, calculates the convective and radiative heat
transfer between the gas and wall by taking into account of the
combustion chamber surface temperature swings. Using the two-zone
combustion model, the combustion parameters and the chemical
equilibrium compositions were determined. The chemical equilibrium
compositions were used to calculate the Nitric oxide formation rate by
assuming a modified Zeldovich mechanism. The accuracy of this
model is scrutinized against actual test results from the engine. The
factors which affect thermal efficiency and exhaust emissions were
deduced and their influences were discussed. In the final analysis it is
seen that there is an excellent agreement in all of these evaluations.
Abstract: This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of sensitivity analysis on port operation quantity provide useful information for managers to choose the best scenario for port planning with the lowest investment risks. Despite all limitations-due to data availability-the model offers a straightforward decision tools to port planners aspiring to achieve optimum port planning steps.
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: Restructured electricity markets may provide
opportunities for producers to exercise market power maintaining
prices in excess of competitive levels. In this paper an oligopolistic
market is presented that all Generation Companies (GenCos) bid in a
Cournot model. Genetic algorithm (GA) is applied to obtain
generation scheduling of each GenCo as well as hourly market
clearing prices (MCP). In order to consider network constraints a
multiperiod framework is presented to simulate market clearing
mechanism in which the behaviors of market participants are
modelled through piecewise block curves. A mixed integer linear
programming (MILP) is employed to solve the problem. Impacts of
market clearing process on participants- characteristic and final
market prices are presented. Consequently, a novel multi-objective
model is addressed for security constrained optimal bidding strategy
of GenCos. The capability of price-maker GenCos to alter MCP is
evaluated through introducing an effective-supply curve. In addition,
the impact of exercising market power on the variation of market
characteristics as well as GenCos scheduling is studied.
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: 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: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.