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Showing 22 results for Subject: Mathematical Modeling and Applications of OR

S. Rahimi, M.m. Lotfi, M.h. Abooie,
Volume 4, Issue 2 (10-2013)
Abstract

Quality function deployment is a well-known customer-oriented design procedure for translating the voice of customers into a final production. This is a way that higher customer satisfaction is achieved while the other goals of company may also be met. This method, at the first stage, attempts to determine the best fulfillment levels of design requirements which are emanated by customer needs. In real-world applications, product design processes are performed in an uncertain and imprecise environment, more than one objective should be considered to identify the target levels of design requirements, and the values of design requirements are often discrete. Regarding these issues, a fuzzy mixed-integer linear goal programming model with a flexible goal hierarchy is proposed to achieve the optimized compromise solution from a given number of design requirement alternatives .To determine relative importance of customer needs, as an important input data, we apply the well-known fuzzy AHP method. Inspired by a numerical problem, the efficiency of our proposed approach is demonstrated by several experiments. Notably, the approach can easily and efficiently be matched with QFD problems.
N. Shirvani, S. Shadrokh,
Volume 4, Issue 2 (10-2013)
Abstract

We focus on a three-stage supply chain problem for fast moving consumer goods including a supplier, a manufacturer and customers. There are different orders over identical cycles, to be processed in production site. The problem is to find a joint cyclic schedule of raw material procurement and job scheduling minimized the total cost comprised of raw material ordering cost and holding cost, production cost, holding cost of finished products, tardiness cost and rejection cost. An integrated mixed integer programing model is proposed and optimal solution of some instances are provided by solving the model.
A Forghani, F Dehghanian,
Volume 5, Issue 2 (10-2014)
Abstract

In the face of budgetary limitations in organizations, identifying critical facilities for investing in quality improvement plans could be a sensible approach. In this paper, hierarchical facilities with specified covering radius are considered. If disruption happens to a facility, its covering radius will be decreased. For this problem, a bi-objective mathematical formulation is proposed. Critical facilities are equivalent to the facilities which attacking them causes the most reduction in the quality of the system performance. Consequently, this problem is studied in the interdiction problem framework. To solve the multi-objective model the weighting-sum approaches are applied. The first interdictor's objective function helps decision makers to identify the vulnerability of the system. Moreover, the second objective function may assist in minimizing the cost of applied quality improvement plans.


Ms. Maryam Akbari-Jafarabadi, Prof. Reza Tavakkoli-Moghaddam, Mr. Mehdi Mahmoodjanloo, Mr. Yaser Rahimi,
Volume 6, Issue 2 (9-2015)
Abstract

In general, any system may be at risk in a case of losing the critical facilities by natural disasters or terrorist attacks. This paper focuses on identifying the critical facilities and planning to reduce the effect of this event. A three-level model is suggested in the form of a defender-attacker-defender. It is assumed that the facilities are hierarchical and capable of nesting. Also, the attacker budget for the interdiction and defender budget for fortification is limited. At the first level, a defender locates facilities in order to enhance the system capability with the lowest possible cost and full covering customer demand before any interdiction. The worst-case scenario losses are modeled in the second-level. At the third level, a defender is responsible for satisfying the demand of all customers while minimizing the total transportation and outsourcing costs. We use two different approaches to solve this model. In the first approach, the third level of the presented model is coded in Gams software, its second level is solved by an explicit enumeration method, and the first level is solved by tabu search (TS). In the second approach the first level is solved by the bat algorithm (BA). Finally, the conclusion is provided.


Dr Saiedeh Gholami, Mr. Mahdi Jalalian, Dr Reza Ramezanian,
Volume 7, Issue 1 (4-2016)
Abstract

In the past decade, fuel consumption and CO2 emission have increased in the airline industry. Large CO2 footprint has a damaging effect on the environment. Global concerns over this issue has made the airline industry to be greener. Most efforts of the green airline industry are improving the fuel consumption to reduce the CO2 emission and its environmental damage. Here, we use cruise speed control to control the fuel consumption and CO2 emission. Each aircraft has a different speed level needing a different fuel consumption. Service quality is studied besides the energy consumption. We investigate two objectives including total energy consumption (TEC) and passenger service level (PSL). TEC and PSL are conflicting in nature. We develop a mixed-integer nonlinear programming model to integrate schedule design, aircraft assignment and maintenance routing problems. We make use of the augmented ε-constraint method to solve the problem. To evaluate the model, a real data based on the Emirates airline flights is used. The results are compared using four different scenarios


Mr. Mirmohammad Musavi, Dr. Reza Tavakkoli-Moghaddam, Ms. Farnaz Rayat,
Volume 8, Issue 1 (4-2017)
Abstract

We present a bi-objective model for a green truck scheduling and routing problem at a cross-docking system. This model determines three key decisions at the cross dock: (1) defining a sequence and schedule of inbound trucks at the receiving door, (2) specifying a sequence and a schedule of outbound trucks at the shipping door, and (3) determining the routes of the outbound truck while serving customers. The first objective function is related to responsiveness of the network that minimizes time window violations and the second objective function minimizes total fuel consumption of trucks in order to consider the environmental factor of the network. Also, a learning effect is considered in loading and unloading process times. To solve the bi-objective model, an archived multi-objective simulated annealing (AMOSA) is used and modified. Finally, a number of test problems are solved and the efficiency of the proposed AMOSA is compared with the e-constraint method.


Prof. Cornelis Roos,
Volume 8, Issue 2 (5-2017)
Abstract

Many regions in the world are protected against flooding by a dike, which may be either natural or artificial. We deal with a model for finding the optimal heights of such a dike in the future. It minimizes the sum of the investments costs for upgrading the dike in the future and the expected costs due to flooding. The model is highly nonlinear, nonconvex, and infinite-dimensional. Despite this, the model can be solved analytically if there is no backlog in maintenance. If there is a backlog in maintenance, then the optimal solution can be found by minimizing a convex function over a finite interval. However, if the backlog becomes extremely large we show that the model breaks down. Our model has been used in The Netherlands to define legal safety standards for the coming decades.
Dr. Chefi Triki, Dr. Abdulwahab Al-Maimani, Dr. Jamila Akil,
Volume 8, Issue 2 (5-2017)
Abstract

We deal with developing a Decision Support System (DSS) to promote the ridesharing among both students and staff of a big organization. The DSS includes a set of functions that allow the management of the riders’ requests and drivers’ availability and embeds a novel two-phase optimization approach that helps in defining the optimal riders-drivers matching. The first phase consists of solving a constraint programming model that generates all the feasible routes. Then, the second phase a bin packing based model is solved to find the optimal route for every driver in order to serve the set of riders assigned to her vehicle. We conclude by an illustrative example that shows the validity of our DSS and, finally, by a discussion on the possible commercialization of such a platform.
Dr. Hadi Nasseri, Mr. Ghorbanali Ramzanniakeshteli,
Volume 9, Issue 1 (7-2018)
Abstract

 We are concerned with solving Fuzzy Flexible Linear Programming (FFLP) problems. Even though, this model is very practical and is useful for many applications, but there are only a few methods for its situation. In most approaches proposed in the literature, the solution process needs at least, two phases where each phase needs to solve a linear programming problem. Here, we propose a method to solve the given problem in just one phase using only one problem. Furthermore, using our approach, sensitivity analysis of Fuzzy Flexible Linear Programming (FFLP) problem is simpler. For an illustration of our method, some numerical examples given. In particular, a practical problem is formulated and is solved by our method and several other methods and the obtained results are compared.
Dr. Tahereh Sayar, Dr. Jafar Fathali, Dr. Mojtaba Ghiyasi,
Volume 9, Issue 1 (7-2018)
Abstract


     One of the most reliable indicators of the evaluation of the same units is the use of mathematical programming based method called data envelopment analysis (DEA). DEA measures the efficiency score of a set of homogeneous decision making units (DMUs) based on observed input and output. The DEA method has been added to the literature by integrating Farrell's method in such a way that each evaluation unit has multiple inputs and multiple outputs. With the advancement and evolution of this approach, DEAis now one of the active areas of research in measuring performance and has been dramatically welcomed by world researchers. Charnes, Cooper, and Rhodes (CCR) [1] first proposed DEA method to evaluate the relative efficiency for not-for-profit organizations. So far, many studies and researches have been carried out in various associations and universities around the world about DEA and its applications. The simplicity of understanding and implementing the DEA method, along with its high precision and wide application in various political, cultural, social and economic fields has led many researchers to use this method to achieve their goals. So far, more than 50,000 articles, books, theses and more have been published on DEA theories and applications, calculations and issues.
Dr. M. Niksirat,
Volume 9, Issue 1 (7-2018)
Abstract

In this paper bus scheduling problem under the constraints that the total number of buses needed to perform all trips is known in advance and the energy level of buses is limited, is considered. Each depot has a different time processing cost. The goal of this problem is to find a minimum cost feasible schedule for buses. A mathematical formulation of the problem is developed. When there are two depots, a polynomial time algorithm is developed for the problem and theoretical results about the complexity and correctness of the algorithm is presented. Also, several examples are introduced for illustrating validity of the algorithm.
Mrs. S. Madadi, Dr. F. Hosseinzadeh Lotfi, Dr. M. Rostamy-Malkhalifeh, Dr. M. Fallah Jelodar,
Volume 9, Issue 1 (7-2018)
Abstract

Resource allocation is a problem that commonly appears in organization with a centralized decision making (CDM), who controls the units. The aim of central decision making is to allocate resources in such a way that the organization get the most benefit. Some Data Envelopment Analysis (DEA) researchers presented DEA-based resource allocation models by paying attention to energy saving and environmental pollution reduction. In this paper, we expanded a resource allocation model for 25 branches of an Iranian Tejarat bank, so that determined how much decision making (DM) can save on energy and manpower hours, so that undesirable outputs like non-performing loans are significantly reduced in a way that achieve the minimum reduction of desirable outputs while unchanged the performance of each unit after re-allocation. The result of the implementation of the model shows that in total with a 10% and 23% reduction in staff and costs respectively can result in the 0.09% reduction of deposits and 56% of non-performing loans.
Dr. Reza Ghanbari, Mrs. Effat Sadat Alavi,
Volume 9, Issue 1 (7-2018)
Abstract

A new integer program is presented to model an independent resources assignment problem with resource shortages in the context of municipal fire service. When shortage in resources exists, a critical task for fire department's administrator in a city is to assign the available resources to the fire stations such that the effect of the shortage to cover (in providing service, in extinguishing fire and so on) is minimized. To solve the problem, we propose a polynomial time greedy algorithm.
Dr. Davood Darvishi,
Volume 9, Issue 1 (7-2018)
Abstract

Linear programming problems with interval grey numbers have recently attracted some interest. In this paper, we study linear programs in which right hand sides are interval grey numbers. This model is relevant when uncertain and inaccurate factors make difficult the assignment of a single value to each right hand side. Some methods have been developed for solving these problems. In this paper, we propose a new approach for solving interval grey number linear programming problems is introduced without converting them to classical linear programming problems. A numerical example is provided to illustrate the proposed approach.
Dr Abolfazl Fathollahzadeh,
Volume 9, Issue 2 (6-2018)
Abstract

This paper is directed to the question of how to model and design an efficient tool for the intelligent mapping which is based on both dynamic and efficient storage of data and soft computing. The former is performed by our method that learns how to store, search and delete the data. After pointing out the limitation of the crisp evaluation of the distance between two points, we argue in favor of soft computing which is based on the extension of metric space to
interval one and then to the fuzzy metric. A-Star algorithm is used to illustrate our model along with the injection of competitive data structures.
Dr. Mehdi Foumani, Dr. Reza Tavakkoli Moghaddam,
Volume 10, Issue 1 (7-2019)
Abstract

This paper analyzes the performance of a robotic system with two machines in which machines are configured in a circular layout and produce non-identical parts repetitively. The non-destructive testing (NDT) is performed by a stationary robotic arm located in the center of the circle, or a cluster tool. The robotic arm integrates multiple tasks, mainly the NDT of the part and its transition between a pair of machines. The robotic arm cannot complete the transition if it identifies a fault in the part. The main feature of the NDT technology is that its required time is changed by altering the testing cost. This generates a trade-off between cost and cycle time. Initially, the problem of robotic arm scheduling and part sequencing is jointly solved to supports the decision making for reliability improvement of small-scale robotic systems with NDT technologies. We show how the case of non-identical parts can be converted into a travelling salesman problem (TSP). Then, we provide a generalization of the framework based on three characteristics: pickup criterion, layout and travel time metric. The results are extended for the interval and no-wait pickup criteria, and then some notes are provided for travel time saving of different layout and travel time metric. It is shown whether circular systems are equivalent to linear systems, or they dominate linear cases in general terms.
Mrs. Mahdieh Zarei, Dr. Hamid Mashreghi, Dr. Saeed Emami,
Volume 10, Issue 1 (7-2019)
Abstract

Nowadays, airline industries should overcome different barriers regarding the fierce competition and changing consumer behavior. Thus, they attempt to focus on joint decision making which enables them to set pricing and capacity allocation to maximize their profits. In this research, we develop a model to optimize pricing and capacity allocation in a duopoly of single-flight leg for two competitive airlines. The problem considers actual assumptions about flexible partitions in flight’s cabins and additionally demand uncertainty. There is a flexible partitioning of business and economy cabins and demand is assumed price-dependent with additive uncertainty. The capacity and pricing decisions are simultaneously determined through indirect channels. Moreover, a numerical study is developed to investigate how market components and competition conditions change pricing, capacity, and profit levels. The results show that increasing market volume like decreasing price sensitivity provides higher levels of price and profits. Moreover, intensified competition never leads to higher prices. Thus, a competitive network of airlines provides better impact on market mechanism to achieve competitive prices for both economy and business classes.
Mr. Aidin Azari Marhabi, Dr. Abdollah Arasteh, Dr. Mohammad Mahdi Paydar,
Volume 10, Issue 1 (7-2019)
Abstract

This paper presents a structure that empower designing supervisory groups to survey the estimation of real options in projects of enormous scale, incompletely standardized frameworks actualized a couple of times over the medium term. Specific options writing is done using a methodology of planning the design and making prior decisions regarding the arrangements of specific options, with a recreation-based value measure designed to be near-current construction rehearsals and to resolve financial problems in particular cases. To study the case and demonstrate the actual application of this method, drug chain modeling at the tactical level was investigated. The physical and financial flow and their disturbance are simultaneously modulated. In order to complete the financial flow, financial ratios are also entered into the model. Problem uncertainty has been modeled using one of the most recent robust optimization approaches called Robust Possibilistic Programming (RPP) in combination with real options theory. The model was applied to a case study and its results were analyzed and validated by GAMS software. The results show that without violating the limitations of the problem, it shows appropriate decisions to deal with the problem.
Mrs. Mana Andarkhora, Dr. Amirhossein Azadnia, Dr. Saeid Gholizadeh, Dr. Pezhman Ghadimi,
Volume 10, Issue 1 (7-2019)
Abstract

One important step to achieve a sustainable transportation system is to control the impact and evaluate the effect of various influencing factors toward three dimensions of sustainability. Within this context, diverse analytical approaches have been developed to assess the sustainability level of various transportation systems, however, sustainability evaluation based on fuzzy multiple criteria decision-making approaches are still limited. In current research activity, an integrated quantitative evaluation technique is proposed to narrow the identified gap. The developed decision-making approach is consisted of two main phases. Firstly, fuzzy analytic hierarchy process is utilized to weigh the sustainability dimensions resulting in the incorporation of the experts’ knowledge along with the evaluation process. Then, a proposed fuzzy inference mechanism is proposed to provide an indication on the performance of an evaluated road transportation system. The developed approach is applied on a real-world case study. Finally, future works are presented together with some concluding remarks.
Mr. Masoud Alinezahd,
Volume 10, Issue 1 (7-2019)
Abstract

Nowadays, manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of supply chain planning. On the other hand, increasing worldwide environmental, lack of food resources and social concerns are motivating manufacturers and consumers to implement recycling strategies such as product recovery, waste management, or usage of recycled materials. In this study, the closed-loop supply chain network has been proposed which consists of four echelons (suppliers, plants, distribution centers, and customers) in the forward chain and three echelons (collection centers, inspection centers, and disposal centers) in the backward chain. We present a multi-product and multi-period mixed-integer linear programming problem in this paper. The objective of this study is to maximize the profit in the closed-loop supply chain network. The proposed model is applied to an illustrative example based on inspiration from the dairy industry in Iran. The solution of the proposed model is achieved by using Gams software. The results give important insight for fostering the decision making process.

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