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A Mixed Integer Programming Model Formulation for Solving the Lot-Sizing Problem
This paper addresses a mixed integer programming (MIP) formulation for t...
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Mixed-Integer Linear Programming Models for Multi-Robot Non-Adversarial Search
In this letter, we consider the Multi-Robot Efficient Search Path Planni...
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New approaches for the uncapacitated three-level lot-sizing and replenishment problem with a distribution structure
We consider the uncapacitated three-level lot-sizing and replenishment p...
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Sensor and Sink Placement, Scheduling and Routing Algorithms for Connected Coverage of Wireless Sensor Networks
A sensor is a small electronic device which has the ability to sense, co...
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Vehicle Scheduling Problem
We define a new problem called the Vehicle Scheduling Problem (VSP). The...
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Planning Optimal Paths for Multiple Robots on Graphs
In this paper, we study the problem of optimal multi-robot path planning...
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Developing a Mathematical Negotiation Mechanism for a Distributed Procurement Problem and a Hybrid Algorithm for its Solution
Considering the players' bargaining power, designing a bi-level programm...
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5G Network Planning under Service and EMF Constraints: Formulation and Solutions
We target the planning of a 5G cellular network under 5G service and ElectroMagnetic Fields (EMFs) constraints. We initially model the problem with a Mixed Integer Linear Programming (MILP) formulation. The pursued objective is a weighed function of gNB installation costs and 5G service coverage level. In addition, we precisely model restrictive EMF constraints and we integrate scaling parameters to estimate the power radiated by 5G gNBs. Since the considered planning problem is NP-Hard, and therefore very challenging to be solved even for small problem instances, we design an efficient heuristic, called PLanning Algorithm Towards EMF Emissions Assessment (PLATEA), to practically solve it. Results, obtained over a realistic scenario that includes EMF exposure from pre-5G technologies (e.g., 2G, 3G, 4G), prove that PLATEA retrieves a planning that ensures 5G service and restrictive EMF constraints. However, we demonstrate that the results are strongly affected by: i) the relative weight between gNB installation costs and 5G service coverage level, ii) the scaling parameters to estimate the exposure generated by 5G gNBs, and iii) the amount of exposure from pre-5G technologies.
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