# Hadi NasseriUniversity of Mazandaran | UMZ · Faculty of Mathematical Sciences

Hadi Nasseri

Professor

## About

157

Publications

42,587

Reads

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2,327

Citations

Citations since 2017

Introduction

**Skills and Expertise**

## Publications

Publications (157)

In the past decade, sustainable supply chain management has received much attention from practitioners and academics due to the heightened emphasis on environmental, economic, and social sustainability by customers, for-profit and non-profit institutions, community organizations, legislation, and government oversight. Evaluating and selecting a sui...

Because of the intricate nature of real-world scenarios, experts could encounter many ambiguities throughout the decision-making (DM) process. Adopting a DM strategy in conditions of indeterminacy so that the decision makers are limited to a small number of experts is always helpful in real life. Neutrosophic conception is a convenient technique fo...

In this paper, a fractional multi-commodity network flow problem with multi-choice parameters is studied under hybrid fuzzy-stochastic conditions. In this problem, coefficients of the objective function in both the nominator and denominator take the form of multi-choice parameters, with the alternative choices for the nominator and denominator of t...

This study examines the impacts of the built environment on pedestrian urban travels using a fuzzy AHP approach, by taking into account fifteen different variables based on three criteria: network design, environment, and safety. We gathered data from academic and industry experts using a fuzzy-based pairwise comparative survey.
Advantage: We adopt...

In developing countries, the demand for old aged people requiring private health care at home is dramatically growing with the improvement of living standards. Since vehicles are used for transferring the medical staff (or doctors) to patient homes, it may be interesting to select a vehicle type based on the cost, capacity, and environmental sustai...

As we are faced with more uncertainty problems in the real world, it is necessary to provide models that can provide appropriate solutions for dealing with these issues. In this study, we proposed a new approach to solving linear programming problem in the fuzzy environment based on solving a related multi-objective model. This kind of prob...

Goal programming (GP) is one of the most common and fundemental approaches to solve Multi Objective Decision Making (MODM) problems. However , in some cases in real world situation, there are more than just one aspiration level for each objective function. Recently, some authors have been introduced Multi Choice Goal Programming (MCGP) models to so...

Some extensions of fuzzy sets such as interval-valued fuzzy sets, intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy sets, type n-fuzzy sets, and neutrosophic sets provided powerful and practical tools for dealing with uncertainty in decision-making problems. Neutrosophic set is defined with three-dimensional membership functions to de...

Recently fuzzy interval flexible linear programs have attracted many interests. These models are an extension of the classical linear programming which deal with crisp parameters. However, in most of the real-world applications, the nature of the parameters of the decision-making problems is generally imprecise. Such uncertainties can lead to incre...

The aim of this paper is to introduce a formulation of linear programming problems involving intuitionistic fuzzy variables. Here, we will focus on duality and a simplex-based algorithm for these problems. We classify these problems into two main different categories: linear programming with intuitionistic fuzzy numbers problems and linear programm...

In this paper, due to increasing competition in the business world, which makes decision makers dealing with multiple options/information for optimal decisions on a single task, we will look at multi-choice programming in hybrid fuzzy random environment. Alternative choices multi-choice parameters are considered as fuzzy random variables. By using...

One of the main topics discussed in a supply chain is the production-distribution problem. Producing and distributing the products plays a key role in reducing the costs of the chain. To design a supply chain, a network of efficient management and production-distribution decisions is essential. Accordingly, providing an appropriate mathematical mod...

This paper deals with knapsack problem in fuzzy nature, where both the objective function and constraints are considered to be fuzzy. Three different models for fuzzy knapsack problem are proposed including, expected value model, chance-constrained model, and dependent-chance model. Credibility ranking method is applied to convert the fuzzy models...

The current paper focuses on a multiobjective transportation problem which is a special type of vector minimum problem. In order to deal with such a problem, a new model based on fuzzy goal programming is suggested. Different solutions are obtained according to the priorities of the decision maker in the proposed model. With respect to its properti...

One of the main topics discussed in a supply chain is the production-distribution problem. Producing and distributing the products plays a key role in reducing the costs of the chain. To design a supply chain, a network of efficient management and production-distribution decisions is essential. Accordingly, providing an appropriate mathematical mod...

Many problems in operations research including problems from management, production planning and scheduling, transportation, location, and many others necessitate decision making in the presence of uncertainty. Therefore, many theories and methodologies have been developed to deal with optimization problems under uncertainty in general. To understa...

Purpose
For extending the common definitions and concepts of grey system theory to the optimization subject, a dual problem is proposed for the primal grey linear programming problem.
Design/methodology/approach
The authors discuss the solution concepts of primal and dual of grey linear programming problems without converting them to classical lin...

Cross-efficiency is a famous ranking method for data envelopment analysis (DEA) that deletes unrealistic weights pattern with no need to a priori information related to weights restrictions. This method analyzes each decision making unit (DMU) taking into account the best weights resulted from assessing other DMUs. In cross-efficiency ev...

This paper presents a new method for group multi-attribute decision-making (GMADM) based on interval neutrosophic sets, where decision makers determine the weights and the evaluating values of the attributes with respect to the available alternatives by using interval neutrosophic values. In comparison with other existing methods involving group mu...

In this paper, we consider a Fuzzy Stochastic Linear Fractional Programming problem (FSLFP). In this problem, the coefficients and scalars in the objective function are the triangular fuzzy number and technological coefficients and the quantities on the right side of the constraints are fuzzy random variables with the specific distribution. Here we...

For the linear programming problems in the crisp scenario, the aim is to maximize or minimize a linear objective function under linear constraints. But in many practical situations, such as those concerning management sciences, diet problem, network optimization, assignment problem, transportation, and etc., the decision maker may not be in a posit...

Fuzzy sets theory has been applied to many disciplines such as control theory and management sciences, mathematical modeling, industrial applications and etc. We usually face some difficulties when a such real-world problems are formulated into a mathematical programming problem. One of the difficulties is caused by the uncertainty in knowledge, in...

Since the fuzziness may appear in many ways for the parameters of linear programming models, hence the definition of fuzzy linear programming is not unique. One of these models is Semi-Fully Fuzzy Linear Programming (SFFLP) problem where the coefficients in the objective function, the right hand side vector and the decision variables are a kind of...

In the real world, there are many problems which have linear programming models and sometimes it is necessary to formulate these models with parameters of uncertainty. Many numbers from these problems are linear programming problems with fuzzy variables.

One of the most interesting models of the linear programming in uncertainty environment is the flexible linear programming problem. It is shown that by using a suitable membership function for their constraints we can obtain an equivalent linear programming problem with fuzzy variables (FVLP).

The aim of this chapter is to study linear programming problem with fuzzy coefficients as one of the convenient model of fuzzy linear programs. In this way, we first introduce a general form of Fuzzy Number Linear programming (FNLP) problems and then give the fundamental concepts which are useful in throughout of the chapter.

Geometric programming problems are well-known in mathematical modeling. They are broadly used in diverse practical fields that are contemplated through an appropriate methodology. In this paper, a multi-parametric vector α is proposed for approaching the highest decision maker satisfaction. Hitherto, the simple parameter α , which has a scalar role...

Recently fuzzy interval flexible linear programs have attracted many interests. These models are an extension of the classical linear programming which deal with crisp parameters. However, in most of the real-world applications, the nature of the parameters of the decision-making problems are generally imprecise. Such uncertainties can lead to incr...

Data envelopment analysis (DEA) is a widely used mathematical programming technique for measuring the relative efficiency of decision making units (DMUs) which consume multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally used in classical DEA models, real-life problems often involve uncertainties cha...

Data envelopment analysis (DEA) divides the units under evaluation
into two groups: 1) the efficient units; 2) inefficient units. Inefficient units can be ranked in terms of effectiveness while efficient units, because of the same efficiency score being equal to one, have the same rank. Several methods have been proposed to rank efficient decision...

In this paper, a novel method to solve Fully Fuzzy Mixed Integer Linear Programming (FFMILP) problems is presented. Our method is based on the definition of membership function and a fuzzy interactive technique for solving the classical multiobjective programming. It is worthwhile to note that this is the first time that the fully fuzzy mixed integ...

Cross-efficiency evaluation, an extension of the data envelopment analysis (DEA), has found an appropriate function in ranking decision making units (DMU). However, DEA suffers from a potential flaw, that is, the existence of multiple optimal solutions. Different methods have been proposed to obtain a unique solution (based on a specific criterion)...

In this paper, we present a new method to solve a fuzzy linear programming problem with fuzzy coefficients in the constraints and the objective function based on solving an associated multi-objective model. In particular, we present a weighted method for linear semi-infinite programming (LSIP) model to solve the original problem. Finally, a numeric...

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of Decision Making Units (DMUs) with multiple deterministic inputs and multiple outputs. However, in real-world problems, the observed values of the input and output data are often vague or random. Indeed, Decision Makers (DMs) may encounter a hybrid...

In order to achieve a compromised solution for a multi-objective linear programming with fuzzy right hand sides, Tchebycheff norm and a new approach based on \( \alpha \)-cut is suggested to minimize the distance from the current estimate of the objective values from the ideal point. Since the obtained solutions by the Tchebycheff approach are weak...

Formulation of a balanced diet, which provides all nutritional requirements of livestock in accordance with its special physiological conditions, is not possible totally. According to the frequency and salient increasing of the breeding center in the country and the shortage of forage and food materials considering the available resources, diet opt...

Purpose
This paper discusses the animal diet problem in grey environment which is adapted to the real situations. In particular, a new approach concerning to solve these problems using is proposed.
Design/methodology/approach
With the objective to produce the least cost diet, in the traditional model for optimizing diet problem, the price of foo...

In this paper, a grey linear programming problem with grey coefficients is discussed. In particular, the duality results as one of the important results on linear programming with grey parameters is established. First, some definitions and concepts of Grey System Theory are introduced and then a dual problem is defined for the primal grey linear pr...

Data envelopment analysis (DEA) is a widely used technique for measuring the relative efficiencies of decision-making units (DMUs) with multiple inputs and multiple outputs. The classical DEA models were initially formulated only for desirable inputs and outputs. However, undesirable outputs may be present in the production process which needs to b...

There are many reasons for the growing interest in developing new product projects for any firm. The most embossed reason is surviving in a highly competitive industry which the customer tastes are changing rapidly. A well-managed supply chain network can provide the most profit for firms due to considering new product development. Along with profi...

In this study, we show that ranking fuzzy numbers with the area method using circumcenter of centroids presented by Rao and Shankar failed to rank effectively the generalized fuzzy numbers. By proving a theorem and using some numerical examples, we demonstrate that their proposed method cannot rank consistently some fuzzy numbers or is not consiste...

Ranking fuzzy numbers is an important issue in decision making analysis, optimisation, artificial intelligence and operations research. Therefore, many methods have been proposed for ranking fuzzy numbers in the literature. However, all of these methods have some limitations and shortcomings. Thus, in this paper, based on coordinates of the centre...

Linear assignment problem is one of the most important practical
models in the literature of linear programming problems. Input data in
the cost matrix of the linear assignment problem are not always crisp and
sometimes in the practical situations is formulated by the grey systems theory
approach. In this way, some researchers have used a whitening...

In this paper, we considered a Stochastic Interval-Valued Linear Fractional Programming problem(SIVLFP). In this problem, the coefficients and scalars in the objective function are fractional-interval, and technological coefficients and the quantities on the right side of the constraints were random variables with the specific distribution. Here we...

In the process of milk production, the highest cost relates to animal feed. Based on reports provided by the experts, around seventy percent of dairy livestock costs included feed costs. In order to minimize the total price of livestock feed, according to the limits of feed sources in each region or season, and also the transportation and maintenan...

New product development has become increasingly important recently due to highly competitive market place and economic reasons. Development and production of new products in the planning horizon require an efficient and responsiveness supply chain network. As new products appear in the market, the old products could become obsolete, and then phased...

In this paper, a linear programming problem is considered involving interval grey numbers as
an extension of the classical linear programming problem to an inexact environment as well
as fuzzy and stochastic environment

This study aims to design a multi-echelon, multi-objective supply chain model that incorporates new product development and its effects on supply chain configuration. To survive in a highly competitive industry, strategies to either collaborate or compete with rival firms within a network should be considered in the new product development process,...

Linear programming is one of the appropriate methods which can be used in the formulation diet problem due to the requirements for animals at the least cost. Since often data are experimental, imprecise and approximated, so it will be used the interval and fuzzy models up to diet problem having necessary flexibility. When data is little and incompl...

Data envelopment analysis (DEA) is a widely used technique for measuring the relative efficiencies of decision making units (DMUs) with multiple inputs and multiple outputs. However, in real-world problems, the observed values of the input and output data are often vague or random. Indeed, decision makers (DMs) may encounter a hybrid uncertain envi...

Data envelopment analysis (DEA) is a widely used technique for measuring the relative efficiencies of decision making units (DMUs) with multiple inputs and multiple outputs. However, in real-world problems, the observed values of the input and output data are often vague or random. Indeed, decision makers (DMs) may encounter a hybrid uncertain envi...

This paper deals with multi-echelon integrated purchase, production and distribution planning model in a supply chain system. The manufacturer procures raw material from suppliers then proceed to convert it as finished product, and finally delivers to the distribution centers in order to minimize the total cost of the chain, which faces imprecise a...

Kaur and Kumar, 2013, use Mehar’s method to solve a kind of fully fuzzy linear programming (FFLP) problems with LR fuzzy parameters. In this paper, a new kind of FFLP problems is introduced with a solution method proposed. The FFLP is converted into a multiobjective linear programming (MOLP) according to the order relation for comparing the LR flat...

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approac...

Some new concepts in regards to ᾱ-feasibility and ᾱ-efficiency of solutions in fuzzy mathematical programming problems are introduced in this paper, where ᾱ is a vector of distinct satisfaction degrees. Based on the defined concepts, a new method is suggested to solve fuzzy mathematical programming problems. In this sense, the proposed approach ena...

The purpose of the present paper is to investigate optimality conditions and duality theory in fuzzy number quadratic programming (FNQP) in which the objective function is fuzzy quadratic function with fuzzy number coefficients and the constraint set is fuzzy linear functions with fuzzy number coefficients. Firstly, the equivalent quadratic program...

Modeling and solving optimization problems is one of the most important issues in our real world problems. This paper presents a new method for solving Fully Fuzzy Linear Programming (FFLP) problems. Although, it has been considered and expanded from many various points of view in more than a decade, but still it is useful to develop new procedures...

Geometric programming is a methodology for solving algebraic nonlinear optimization problems. It provides a powerful tool for solving nonlinear problems where nonlinear relations can be well presented by an exponential or power function. Many applications of geometric programming are engineering design problems in which some of the parameters are a...

Data envelopment analysis (DEA) is a considerable mathematical programming technique for measuring the relative efficiencies of a set of decision making units (DMUs) with multiple inputs and multiple outputs. Conventional DEA assists decision makers in distinguishing between efficient and inefficient DMUs in a homogeneous group. However, it does no...

In this study, we present a new mixed integer linear programming model for an open shop scheduling problem, considering setup times, processing times, sequence dependent removal times and inaccessibility time for machines. Objective in this problem is minimizing maximum completion times (makespan). Due to uncertainty of the data, in continuation, w...

scheduling consists of assignment resources in order to perform a set of tasks in a given time horizon, that optimizes the usage of available resources. Most of researches in open shop district (area) have stationary and certain status, means the situation that all data are certain and won't change in time horizon. Whereas real world scheduling pro...

Ordering fuzzy quantities and their comparison play a key tool in many applied models in the world and in particular decision-making procedures. However a huge number of researches is attracted to this filed but until now there is any unique accepted method to rank the fuzzy quantities. In fact, each proposed method may has some shortcoming. So we...

The objective of this paper is to deal with a kind of fuzzy linear programming problem involving triangular fuzzy numbers. Then some interesting and fundamental results are achieved which in turn lead to a solution of fuzzy linear programming models without converting the problems to the crisp linear programming models. Finally, the theoretical res...

The aim of this paper is introducing the new concepts of feasibility and efficiency with distinct satisfaction degrees corresponding to different fuzzy constraints of the problem. This approach enables decision maker (DM) to take into account more flexible solutions by allowing desired distinct satisfactions in constraints.

برنامه ريزي درجه دوم رده خاصي از مسايل برنامه ريزي غيرخطي است که در آن تابع هدف از نوع درجه دوم و قيود خطي مي باشند. مدل هاي متداول برنامه ريزي درجه دوم نيازمند پارامترهايي معين با مقاديري ثابت هستند. اين مدل به طور گسترده براي حل مسايل دنياي واقعي به کار برده مي شوند. از طرف ديگر دسته گسترده اي از مسايل که در زندگي روزمره با آنها سروکار داريم و بر...

In most practical problems of linear programming problems with fuzzy cost coefficients, some or all variables are restricted to lie within lower and upper bounds. In this paper, the authors propose a new method for solving such problems called the bounded fuzzy primal simplex algorithm. Some researchers used the linear programming problem with fuzz...

In the real word, there are many problems which have linear programming models and sometimes it is necessary to formulate these models with parameters of uncertainty. Many numbers from these problems are linear programming problems with fuzzy variables. Some authors considered these problems and have developed various methods for solving these prob...

In this paper, we generalize the bounded dual simplex algorithm for solving minimum cost flow problem with fuzzy cost, which its aim is to find the least fuzzy cost of a commodity through a capacitated network in order to satisfy demands at certain nodes using available supplies at other nodes. This algorithm begins with dual feasibility and iterat...

زمانبندي در واقع به تخصيص منابع در طول زمان براي اجراي مجموعهاي از كارها در وضعيتهاي مختلف
ميپردازد. از آنجا كه محيط كارگاه باز در بسياري از محيطهاي دنياي واقعي رخ ميدهد، ارايه مدل مناسب و دقيق
كمك بزرگي به مديران و صنعتگران خواهد نمود. بيان دادههاي دقيق در مسايل زمانبندي عموماً دور از تصور است.
رخدادهاي پيشبيني نشده و خطاهاي اندازهگيري موجب عدم قط...