## About

47

Publications

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800

Citations

Citations since 2016

Introduction

Mansoor Davoodi Monfared currently works at the Computer Science and Information Technology, Institute for Advanced Studies in Basic Sciences. Mansoor does research in Optimization, Multi-objective optimization and Discrete optimization, Algorithms and Complexity, Computational Geometry.

## Publications

Publications (47)

To manage the propagation of infectious diseases, particularly fast-spreading pandemics, it is necessary to provide information about possible infected places and individuals, however, it needs diagnostic tests and is time-consuming and expensive. To smooth these issues, and motivated by the current Coronavirus disease (COVID-19) pandemic, in this...

Definition of an optimal path in the real-world routing problems is not necessarily the shortest one, because parameters such as travel time, safety, quality, and smoothness also played essential roles in the definition of optimality. In this paper, we use bi-colored graphs for modeling urban and heterogeneous environments and introduce variations...

Although monitoring and covering are fundamental goals of a wireless sensor network (WSN), the accidental death of sensors or the running out of their energy would result in holes in the WSN. Such holes have the potential to disrupt the primary functions of WSNs. This paper investigates the hole detection and healing problems in hybrid WSNs with no...

Finding the shortest path on uncertain transportation networks is a great challenge in theory and practice. There are several resources of uncertainty in the transportation networks such as traffic congestion, weather conditions, vehicle accidents, repairing roads, etc. A natural way to model uncertain networks is utilizing graphs with uncertain ed...

In this paper, we study the problem of bi-objective path planning with the objectives minimizing the length and maximizing the clearance of the path, that is, maximizing the minimum distance between the path and the obstacles. The goal is to find Pareto optimal paths. We consider the case that the first objective is measured using the Manhattan met...

In this paper, we consider the problem of path planning in a weighted polygonal planar subdivision. Each polygon has an associated positive weight which shows the cost of path per unit distance of movement in that polygon. The goal is finding a minimum cost path under the Manhattan metric for two given start and destination points. We propose an O(...

In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of special...

The problem of caging an arbitrary object is one of the major issues in the field of robotics. All of algorithms in this field assume that the object is precise, but due to errors during the computation and construction of objects (parts), it is possible, the object's coordination to be imprecise. Our purpose is to provide an appropriate algorithm...

We study the problem of bounding the number of fingers that suffice to immobilize a serial chain of n polyhedra (P 1 , . . . ., P n ), in which each pair of consecutive polyhedra P i+1 (for 1 ≤ i <; n) in the chain shares exactly one vertex ρ i . This vertex ρ i serves as a rotational joint, or hinge. We consider hinges ρ i with one degree of freed...

This study focuses on the problem of handoff minimization for a set of users moving in a wireless network. This problem is analyzed by considering two cases for the user’s movement under access point capacity constraints: 1) all users move together, and 2) each user can have their chosen path within the network. In the first case, we propose an opt...

Sparse Network Coding (SNC) was first introduced as a mechanism to alleviate the decoding complexity of Random Linear Network Coding (RLNC), by selecting a large fraction of zero-valued coding coefficients in the encoding matrix. One of the by-products of SNC scheme is partial decoding, i.e., the possibility to decode a fraction of source packets a...

Balancing workload among a set of facility centers is one of the practical objectives in location problems. In this paper, we introduce a multi-objective optimization facility location problem which considers two goals: minimizing the maximum distance between each client and its closest center, and maximizing workload balance among the centers. To...

Sparse Network Coding (SNC) is a promising technique for reducing the complexity of Random Linear Network Coding (RLNC), by selecting a sparse coefficient matrix to code the packets. However, the performance of SNC for the Average Decoding Delay (ADD) of the packets is still unknown. In this paper, we study the performance of ADD and propose a Mark...

Smart grids, to facilitate the electricity production, distribution, and consumption, employ information and communication technologies simultaneously. Electricity markets, through stabilizing the electricity prices, attempt to alleviate the challenges of power exchange. On one hand, buyers, by considering their full demand satisfaction, endeavor t...

We study the problem of orienting a part with given admitted shape variations by means of pushing with a single frictionless jaw. We use a very general model for shape variations that is defined by two given convex polygons PI⊆PE. In this model, any valid instance must contain PI while it must be contained in PE. The problem that we solve is to det...

Path planning has become a central problem in motion planning. The classic version of the problem aims to find an obstacle-free path with the minimum length for a given workspace containing a set of obstacles and two sources and destination points. However, some real world applications consider maximizing the path clearance (i.e., the distance betw...

One of the challenging problems in motion planning is finding an efficient path for a robot in different aspects such as length, clearance and smoothness. We formulate this problem as two multi-objective path planning models with the focus on robot's energy consumption and path's safety. These models address two five- and three-objectives optimizat...

Lot-sizing with supplier selection (LS-SS) is a fast-growing offspring of two major problem parents in logistics and supply chain management (‘lot-sizing’ and ‘supplier selection’). The model proposed in this paper is an attempt to extend it to an assembly system, by formulating a multi-objective model for an integrative problem of LS-SS for assemb...

Abstract Given a set R of red points and a set B of blue points in the plane, we study the problem of determining all angles for which there exists an L-shape containing all points from B and no points from R. We propose a worst-case optimal algorithm to solve this problem in O(n2) time and O(n) storage, where n=|R|+|B|. We also describe an output-...

Industrial parts
are
manufactured
to tolerances as no production process is capable of delivering perfectly identical parts. It is unacceptable that a plan for a manipulation task that was determined on the basis of a CAD model of a part fails on some manufactured instance of that part, and therefore it is crucial that the admitted shape variations...

An essential assumption in most algorithms in computational geometry is that the input data is precise which is not always true in real world problems. In this paper we introduce a model - called lambda-geometry model - for handling a dynamic form of imprecision which allows the precision changes in the input data of geometric problems. Also, we st...

Conic sections have many applications in industrial design, however, they cannot be exactly represented in polynomial form. Hence approximating conic sections with polynomials is a challenging problem. In this paper, we use the monomial form of Delgado and Peña (DP) curves and present a matrix representation for them. Using the matrix form and the...

The smart grid makes use of two-way streams of electricity and information to constitute an automated and distributed energy delivery network. Coming up with multi-agent systems for resource allocation, chiefly comprises the design of local capabilities of single agents, and therefore, the interaction and decision-making mechanisms that make them c...

Industrial parts are manufactured to tolerances as no production process is capable of delivering perfectly identical parts. It is unacceptable that a plan for a manipulation task that was determined on the basis of a CAD model of a part fails on some manufactured instance of that part, and therefore it is crucial that the admitted shape variations...

The smart grid makes use of two-way streams of electricity and information to constitute an automated and distributed energy delivery network. Coming up with multi-agent systems for resource allocation, chiefly comprises the design of local capabilities of single agents, and therefore, the interaction and decision-making mechanisms that make them c...

This paper is a study on the problem of path planning for two robots on a grid. We consider the objective of minimizing the maximum path length which corresponds to minimizing the arrival time of the last robot at its goal position. We propose an optimal algorithm that solves the problem in linear time with respect to the size of the grid. We show...

Because of constraints in exact modeling, measuring and computing, it is inevitable that algorithms that solve real world problems have to avoid errors. Hence, proposing models to handle error, and designing algorithms that work well in practice, are challenging fields. In this paper, we introduce a model called the λλ-geometry model to handle a dy...

Finding a path for a robot which is near to natural looking paths is a challenging problem in motion planning. This paper suggests two single and multi-objective optimization models focusing on length and clearance of the path in discrete space. Considering the complexity of the models and potency of evolutionary algorithms we apply a genetic algor...

In this paper, we integrate the three strategies that are important to most firms, namely pricing, lot-sizing and supplier selection. Combining the three objectives of total profit, inconsistency, and deficiency with a set of constraints, we formulate this integrated problem as a multi-objective nonlinear programming model, proposing a genetic algo...

Purpose
– The purpose of this work is to study the capability of heuristic algorithms like genetic algorithm to estimate the electron transport parameters of the Gallium Arsenide (GaAs). Also, the paper provides a simple but complete electron mobility model for the GaAs based on the genetic algorithm that can be suitable for use in simulation, opti...

Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity depends on finding non-dominated fronts, this paper int...

The p-center problem is one of the location problems that have been studied in operations research and computational geometry. This paper describes a compatible discrete space version of the heuristic Voronoi diagram algorithm. Since the algorithm gets stuck in local optimums in some cases, we apply a number of changes in the body of the algorithm...

In this paper, we introduce a new model for handling imprecision in the input data of a geometric problem. The proposed model, which is called λ–geometry, is a generalization of region-based models to handle dynamic imprecision. Further, we study the problem of finding the minimum enclosing circle for a set of imprecise points
that are presented in...

In this study a robust shape reconstruction algorithm is proposed which guarantees a simple polygon as output and works well on both types of input, dot patterns and boundary samples, in the plane. Guaranteed polygonal output makes it favourable for many applications because of its ease of manipulation and use. The proposed algorithm, called simple...

In this paper, two multi-objective mixed integer non-linear models are developed for multi-period lot-sizing problems involving multiple products and multiple suppliers. Each model is constructed on the basis of three objective functions (cost, quality and service level) and a set of constraints. The total costs consist of purchasing, ordering, hol...

Coverage problem which is one of the challenging problems in facility location studies, is NP-hard. In this paper, we focus on a constrained version of coverage problem in which a set of demand points and some constrained regions are given and the goal is to find a minimum number of sensors which covers all demand points. A heuristic approach is pr...

In this paper, we study the weak point matching prob- lem for a given set of n points and a class of equilateral triangles. The problem is to find the maximum car- dinality matching of the points using equilateral trian- gles such that each triangle contains exactly two points and each point lies at most in one triangle. Under the non-degeneracy as...

Given a set R of red points and a set B of blue points in the plane of total size n, we study the problem of deter- mining all angles for which there exists an L-shape con- taining all points from B without containing any points from R. We propose an algorithm to solve the problem in O(n 2 logn) time and O(n) storage. We also describe an output-sen...

The coverage problem is one of the most important types of the facility location problems, which belongs in the NP-hard problems. In this paper, we present a genetic algorithm for solving the constrained coverage problem in continuous space.
The genetic operators are novel operators and specially designed to solve the coverage problem. The new algo...

This paper considers the scenario of supply chain with multiple products and multiple suppliers, all of which have limited capacity. We assume that received items from suppliers are not of perfect quality. Items of imperfect quality, not necessarily defective, could be used in another inventory situation. Imperfect items are sold as a single batch,...

In this paper a multi-period inventory lot sizing scenario, where there are multiple products and multiple suppliers, is solved
with a Real Parameter Genetic Algorithm. We assume that demand of multiple discrete products is known, not exactly, over a
planning horizon and transaction cost is supplier dependent, but does not depend on the variety nor...

In this paper a multi-item fuzzy inventory model under total production cost, total storage space and number of orders constraints
is solved with a Genetic Algorithm. In this model, the production cost and set up cost are directly proportional to the respective
quantities, unit production cost is inversely related to the demand and set up cost is a...

In this paper we introduce a new model for handling imprecision in the input data of a geometric problem. The proposed model, which is called λ-geometry, is a generalization of region based models to handle dy-namic imprecision. Further, we study the problem of finding the largest area axis-aligned bounding box of a set of n imprecise points under...

## Projects

Projects (4)

Suggesting a path to minimize the frequency of visiting important places of a city by police patrols.

- Defining a smart grid scenario consisting of buyers, aiming to purchase the electricity cost-effectively, and sellers, interested in increasing their financial benefits
- Proposing a highly-functional semi-decentralized electricity matching framework based on multi-objective optimization techniques
- Development of a two-stage price updating mechanism to continuously balance the electricity prices offered by negotiators over time
- Implementation of a robust multi-objective electricity matching algorithm benefited from mixed multi-objective integer linear programming methods to make the matching contracts by means of evolutionary computation techniques