Abstract: This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.
Abstract: Logistics centers represent areas that all national and international logistics and activities related to logistics can be implemented by the various businesses. Logistics centers have a key importance in joining the transport stream and the transport system operations. Therefore, it is important where these centers are positioned to be effective and efficient and to show the expected performance of the centers. In this study, the location selection problem to position the logistics center is discussed. Alternative centers are evaluated according certain criteria. The most appropriate center is identified using the axiomatic design method.
Abstract: Facility location is a complex real-world problem
which needs a strategic management decision. This paper provides a
general review on studies, efforts and developments in Facility
Location Problems which are classical optimization problems having
a wide-spread applications in various areas such as transportation,
distribution, production, supply chain decisions and
telecommunication. Our goal is not to review all variants of different
studies in FLPs or to describe very detailed computational techniques
and solution approaches, but rather to provide a broad overview of
major location problems that have been studied, indicating how they
are formulated and what are proposed by researchers to tackle the
problem. A brief, elucidative table based on a grouping according to
“General Problem Type” and “Methods Proposed” used in the studies
is also presented at the end of the work.
Abstract: Parabolic solar trough systems have seen limited
deployments in cold northern climates as they are more suitable for
electricity production in southern latitudes. A numerical dynamic
model is developed to simulate troughs installed in cold climates and
validated using a parabolic solar trough facility in Winnipeg. The
model is developed in Simulink and will be utilized to simulate a trigeneration
system for heating, cooling and electricity generation in
remote northern communities. The main objective of this simulation
is to obtain operational data of solar troughs in cold climates and use
the model to determine ways to improve the economics and address
cold weather issues.
In this paper the validated Simulink model is applied to simulate a
solar assisted absorption cooling system along with electricity
generation using Organic Rankine Cycle (ORC) and thermal storage.
A control strategy is employed to distribute the heated oil from solar
collectors among the above three systems considering the
temperature requirements. This modelling provides dynamic
performance results using measured meteorological data recorded
every minute at the solar facility location. The purpose of this
modeling approach is to accurately predict system performance at
each time step considering the solar radiation fluctuations due to
passing clouds. Optimization of the controller in cold temperatures is
another goal of the simulation to for example minimize heat losses in
winter when energy demand is high and solar resources are low.
The solar absorption cooling is modeled to use the generated heat
from the solar trough system and provide cooling in summer for a
greenhouse which is located next to the solar field.
The results of the simulation are presented for a summer day in
Winnipeg which includes comparison of performance parameters of
the absorption cooling and ORC systems at different heat transfer
fluid (HTF) temperatures.
Abstract: This paper proposes a mathematical model and
examines the performance of an exact algorithm for a location–
transportation problems in humanitarian relief. The model determines
the number and location of distribution centers in a relief network,
the amount of relief supplies to be stocked at each distribution center
and the vehicles to take the supplies to meet the needs of disaster
victims under capacity restriction, transportation and budgetary
constraints. The computational experiments are conducted on the
various sizes of problems that are generated. Branch and bound
algorithm is applied for these problems. The results show that this
algorithm can solve problem sizes of up to three candidate locations
with five demand points and one candidate location with up to twenty
demand points without premature termination.
Abstract: Facility location is one of the important problems affecting the relief operations. The location model in this paper is motivated by arranging the flow of relief materials from the main warehouse to continent warehouse and further to regional warehouse and from these to the disaster area. This flow makes the relief organization always ready to deal with the disaster situation during shortest possible time. The main purpose of this paper is merge the concept of just in time and the campaign system in emergency supply chain,so that when the disaster happens the affected country can request help from the nearest regional warehouse, which will supply the relief material and the required stuff to support and assist the victims in the disaster area. Furthermore, the regional warehouse places an order to the continent warehouse to replenish the material that is distributed to the disaster area. This way they will always be ready to respond to any type of disaster.
Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: This paper provides a framework in order to
incorporate reliability issue as a sign of disruption in distribution
systems and partial covering theory as a response to limitation in
coverage radios and economical preferences, simultaneously into the
traditional literatures of capacitated facility location problems. As a
result we develop a bi-objective model based on the discrete
scenarios for expected cost minimization and demands coverage
maximization through a three echelon supply chain network by
facilitating multi-capacity levels for provider side layers and
imposing gradual coverage function for distribution centers (DCs).
Additionally, in spite of objectives aggregation for solving the model
through LINGO software, a branch of LP-Metric method called Min-
Max approach is proposed and different aspects of corresponds
model will be explored.
Abstract: Facility location problem involves locating a facility
to optimize some performance measures. Location of a public facility
to serve the community, such as a fire station, significantly affects its
service quality. Main objective in locating a fire station is to
minimize the response time, which is the time duration between
receiving a call and reaching the place of incident. In metropolitan
areas, fire vehicles need to cross highways and other traffic obstacles
through some obstacle-overcoming points which delay the response
time. In this paper, fire station location problem is analyzed.
Simulation models are developed for the location problems which
involve obstacles. Particular case problems are analyzed and the
results are presented.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.
Abstract: Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.
Abstract: Recently studies in area of supply chain network
(SCN) have focused on the disruption issues in distribution systems.
Also this paper extends the previous literature by providing a new biobjective
model for cost minimization of designing a three echelon
SCN across normal and failure scenarios with considering multi
capacity option for manufacturers and distribution centers. Moreover,
in order to solve the problem by means of LINGO software, novel
model will be reformulated through a branch of LP-Metric method
called Min-Max approach.
Abstract: Bus networks design is an important problem in
public transportation. The main step to this design, is determining the
number of required terminals and their locations. This is an especial
type of facility location problem, a large scale combinatorial
optimization problem that requires a long time to be solved.
The genetic algorithm (GA) is a search and optimization technique
which works based on evolutionary principle of natural
chromosomes. Specifically, the evolution of chromosomes due to the
action of crossover, mutation and natural selection of chromosomes
based on Darwin's survival-of-the-fittest principle, are all artificially
simulated to constitute a robust search and optimization procedure.
In this paper, we first state the problem as a mixed integer
programming (MIP) problem. Then we design a new crossover and
mutation for bus terminal location problem (BTLP). We tested the
different parameters of genetic algorithm (for a sample problem) and
obtained the optimal parameters for solving BTLP with numerical try
and error.
Abstract: Computation of facility location problem for every
location in the country is not easy simultaneously. Solving the
problem is described by using cluster computing. A technique is to
design parallel algorithm by using local search with single swap
method in order to solve that problem on clusters. Parallel
implementation is done by the use of portable parallel programming,
Message Passing Interface (MPI), on Microsoft Windows Compute
Cluster. In this paper, it presents the algorithm that used local search
with single swap method and implementation of the system of a
facility to be opened by using MPI on cluster. If large datasets are
considered, the process of calculating a reasonable cost for a facility
becomes time consuming. The result shows parallel computation of
facility location problem on cluster speedups and scales well as
problem size increases.