Abstract: Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.
Abstract: The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.
Abstract: This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.
Abstract: Water resource systems modeling has constantly been
a challenge through history for human beings. As the innovative
methodological development is evolving alongside computer sciences
on one hand, researches are likely to confront more complex and
larger water resources systems due to new challenges regarding
increased water demands, climate change and human interventions,
socio-economic concerns, and environment protection and
sustainability. In this research, an automatic calibration scheme has
been applied on the Gilan’s large-scale water resource model using
mathematical programming. The water resource model’s calibration
is developed in order to attune unknown water return flows from
demand sites in the complex Sefidroud irrigation network and other
related areas. The calibration procedure is validated by comparing
several gauged river outflows from the system in the past with model
results. The calibration results are pleasantly reasonable presenting a
rational insight of the system. Subsequently, the unknown optimized
parameters were used in a basin-scale linear optimization model with
the ability to evaluate the system’s performance against a reduced
inflow scenario in future. Results showed an acceptable match
between predicted and observed outflows from the system at selected
hydrometric stations. Moreover, an efficient operating policy was
determined for Sefidroud dam leading to a minimum water shortage
in the reduced inflow scenario.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: Constructing a portfolio of investments is one of the
most significant financial decisions facing individuals and
institutions. In accordance with the modern portfolio theory
maximization of return at minimal risk should be the investment goal
of any successful investor. In addition, the costs incurred when
setting up a new portfolio or rebalancing an existing portfolio must
be included in any realistic analysis.
In this paper rebalancing an investment portfolio in the presence of
transaction costs on the Croatian capital market is analyzed. The
model applied in the paper is an extension of the standard portfolio
mean-variance optimization model in which transaction costs are
incurred to rebalance an investment portfolio. This model allows
different costs for different securities, and different costs for buying
and selling. In order to find efficient portfolio, using this model, first,
the solution of quadratic programming problem of similar size to the
Markowitz model, and then the solution of a linear programming
problem have to be found. Furthermore, in the paper the impact of
transaction costs on the efficient frontier is investigated. Moreover, it
is shown that global minimum variance portfolio on the efficient
frontier always has the same level of the risk regardless of the amount
of transaction costs. Although efficient frontier position depends of
both transaction costs amount and initial portfolio it can be concluded
that extreme right portfolio on the efficient frontier always contains
only one stock with the highest expected return and the highest risk.
Abstract: In this paper, student admission process is studied to
optimize the assignment of vacant seats with three main objectives.
Utilizing all vacant seats, satisfying all programs of study admission
requirements and maintaining fairness among all candidates are the
three main objectives of the optimization model. Seat Assignment
Method (SAM) is used to build the model and solve the optimization
problem with help of Northwest Coroner Method and Least Cost
Method. A closed formula is derived for applying the priority of
assigning seat to candidate based on SAM.
Abstract: Natural gas, as one of the most important sources of
energy for many of the industrial and domestic users all over the
world, has a complex, huge supply chain which is in need of heavy
investments in all the phases of exploration, extraction, production,
transportation, storage and distribution. The main purpose of supply
chain is to meet customers’ need efficiently and with minimum cost.
In this study, with the aim of minimizing economic costs, different
levels of natural gas supply chain in the form of a multi-echelon,
multi-period fuzzy linear programming have been modeled. In this
model, different constraints including constraints on demand
satisfaction, capacity, input/output balance and presence/absence of a
path have been defined. The obtained results suggest efficiency of the
recommended model in optimal allocation and reduction of supply
chain costs.
Abstract: The power system utility has started to think about the green power technology in order to have an eco-friendly environment. The green power technology utilizes renewable energy sources for reduction of GHG emissions. Odisha state (India) is very rich in potential of renewable energy sources especially in solar energy (about 300 solar days), for installation of grid connected photovoltaic system. This paper focuses on the utilization of photovoltaic systems in an Institute building of Bhubaneswar city, Odisha. Different data like solar insolation (kW/m2/day), sunshine duration has been collected from metrological stations for Bhubaneswar city. The required electrical power and cost are calculated for daily load of 1.0 kW. The HOMER (Hybrid Optimization Model of Electric Renewable) software is used to estimate system size and its performance analysis. The simulation result shows that the cost of energy (COE) is $ 0.194/kWh, the Operating cost is $63/yr and the net present cost (NPC) is $3,917. The energy produced from PV array is 1,756kWh/yr and energy purchased from grid is 410kWh/yr. The AC primary load consumption is 1314 kWh/yr and the Grid sales are 746 kWh/yr. One battery is connected in parallel with 12V DC Bus and the usable nominal capacity 2.4 kWh with 9.6 h autonomy capacity.
Abstract: In this paper, the optimum design for renewable energy system powered an aquaculture pond was determined. Hybrid Optimization Model for Electric Renewable (HOMER) software program, which is developed by U.S National Renewable Energy Laboratory (NREL), is used for analyzing the feasibility of the stand alone and hybrid system in this study. HOMER program determines whether renewable energy resources satisfy hourly electric demand or not. The program calculates energy balance for every 8760 hours in a year to simulate operation of the system. This optimization compares the demand for the electrical energy for each hour of the year with the energy supplied by the system for that hour and calculates the relevant energy flow for each component in the model. The essential principle is to minimize the total system cost while HOMER ensures control of the system. Moreover the feasibility analysis of the energy system is also studied. Wind speed, solar irradiance, interest rate and capacity shortage are the parameters which are taken into consideration. The simulation results indicate that the hybrid system is the best choice in this study, yielding lower net present cost. Thus, it provides higher system performance than PV or wind stand alone systems.
Abstract: Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.
Abstract: This paper focuses on the operational and strategic planning decisions related to the quayside of container terminals. We introduce an integrated operational research (OR) and system dynamics (SD) approach to solve the Berth Allocation Problem (BAP) and the Quay Crane Assignment Problem (QCAP). A BAP-QCAP optimization modeling approach which considers practical aspects not studied before in the integration of BAP and QCAP is discussed. A conceptual SD model is developed to determine the long-term effect of optimization on the system behavior factors like resource utilization, attractiveness to port, number of incoming vessels to port and port profits. The framework can be used for improving the operational efficiency of container terminals and providing a strategic view after applying optimization.
Abstract: The paper proposes an approach to ranking a set of potential countries to invest taking into account the investor point of view about importance of different economic indicators. For the goal, a ranking algorithm that contributes to rational decision making is proposed. The described algorithm is based on combinatorial optimization modeling and repeated multi-criteria tasks solution. The final result is list of countries ranked in respect of investor preferences about importance of economic indicators for investment attractiveness. Different scenarios are simulated conforming to different investors preferences. A numerical example with real dataset of indicators is solved. The numerical testing shows the applicability of the described algorithm. The proposed approach can be used with any sets of indicators as ranking criteria reflecting different points of view of investors.
Abstract: Standalone micro-hydrokinetic river (MHR) system is
one of the promising technologies to be used for remote rural
electrification. It simply requires the flow of water instead of
elevation or head, leading to expensive civil works. This paper
demonstrates an economic benefit offered by a standalone MHR
system when compared to the commonly used standalone systems
such as solar, wind and diesel generator (DG) at the selected study
site in Kwazulu Natal. Wind speed and solar radiation data of the
selected rural site have been taken from national aeronautics and
space administration (NASA) surface meteorology database. The
hybrid optimization model for electric renewable (HOMER) software
was used to determine the most feasible solution when using MHR,
solar, wind or DG system to supply 5 rural houses. MHR system
proved to be the best cost-effective option to consider at the study site
due to its low cost of energy (COE) and low net present cost (NPC).
Abstract: The paper describes an approach for defining of k-best night vision devices based on multi-criteria mixed-integer optimization modeling. The parameters of night vision devices are considered as criteria that have to be optimized. Using different user preferences for the relative importance between parameters different choice of k-best devices can be defined. An ideal device with all of its parameters at their optimum is used to determine how far the particular device from the ideal one is. A procedure for evaluation of deviation between ideal solution and k-best solutions is presented. The applicability of the proposed approach is numerically illustrated using real night vision devices data. The proposed approach contributes to quality of decisions about choice of night vision devices by making the decision making process more certain, rational and efficient.
Abstract: While to minimize the overall project cost is always
one of the objectives of construction managers, to obtain the
maximum economic return is definitely one the ultimate goals of the
project investors. As there is a trade-off relationship between the
project time and cost, and the project delivery time directly affects the
timing of economic recovery of an investment project, to provide a
method that can quantify the relationship between the project delivery
time and cost, and identify the optimal delivery time to maximize
economic return has always been the focus of researchers and
industrial practitioners. Using genetic algorithms, this study
introduces an optimization model that can quantify the relationship
between the project delivery time and cost and furthermore, determine
the optimal delivery time to maximize the economic return of the
project. The results provide objective quantification for accurately
evaluating the project delivery time and cost, and facilitate the
analysis of the economic return of a project.
Abstract: Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.
Abstract: Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances to be allocated at these locations. The model aims at maximizing the expected demand coverage based on probability of reaching the emergency location within targetted time, and minimizing the ambulance busyness likelihood value. Among the benefits of the model is the increased accessibility and availability of ambulances, thus, enhanced quality of the EMS ambulance services.
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: Combining energy efficiency with renewable energy
sources constitutes a key strategy for a sustainable future. The wind
power sector stands out as a fundamental element for the
achievement of the European renewable objectives and Portugal is no
exception to the increase of the wind energy for the electricity
generation. This work proposes an optimization model for the long
range electricity power planning in a system similar to the
Portuguese one, where the expected impacts of the increasing
installed wind power on the operating performance of thermal power
plants are taken into account. The main results indicate that the
increasing penetration of wind power in the electricity system will
have significant effects on the combined cycle gas power plants
operation and on the theoretically expected cost reduction and
environmental gains. This research demonstrated the need to address
the impact that energy sources with variable output may have, not
only on the short-term operational planning, but especially on the
medium to long range planning activities, in order to meet the
strategic objectives for the energy sector.