scholarly journals ORNInA: A decentralized, auction-based multi-agent coordination in ODT systems

2021 ◽  
pp. 1-17
Author(s):  
Alaa Daoud ◽  
Flavien Balbo ◽  
Paolo Gianessi ◽  
Gauthier Picard
Keyword(s):  
Synthetic Data ◽  
Continuous Optimization ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Multi Agent ◽  
Run Time ◽  
Agent Coordination

On-Demand Transport (ODT) systems have attracted increasing attention in recent years. Traditional centralized dispatching can achieve optimal solutions, but NP-Hard complexity makes it unsuitable for online and dynamic problems. Centralized and decentralized heuristics can achieve fast, feasible solution at run-time with no guarantee on the quality. Starting from a feasible not optimal solution, we present in this paper a new solution model (ORNInA) consisting of two parallel coordination processes. The first one is a decentralized insertion-heuristic based algorithm to build vehicle schedules in order to solve a particular case of the dynamic Dial-A-Ride-Problem (DARP) as an ODT system, in which vehicles communicate via Vehicle-to-vehicle communication (V2V) and make decentralized decisions. The second coordination scheme is a continuous optimization process namely Pull-demand protocol, based on combinatorial auctions, in order to improve the quality of the global solution achieved by decentralized decision at run-time by exchanging resources between vehicles (k-opt). In its simplest implementation, k is set to 1 so that vehicles can exchange only one resource at a time. We evaluate and analyze the promising results of our contributed techniques on synthetic data for taxis operating in Saint-Étienne city, against a classical decentralized greedy approach and a centralized one that uses a classical mixed-integer linear program (MILP) solver.

scholarly journals Cooperative Multi-Agent Vehicle-to-Vehicle Wireless Network in a Noisy Environment

2021 ◽  
Vol 15 ◽  
pp. 135-148
Author(s):  
Ayman M. Mansour
Keyword(s):  
Intelligent System ◽  
Rapid Development ◽  
Noisy Environment ◽  
Smart System ◽  
Fully Integrated ◽  
Agent Model ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Multi Agent ◽  
Communication Methods

With the rapid development of vehicle communication and the goal of self-driving vehicle, research in this area is still ongoing, as car companies aspire for more studies and effective communication methods between vehicles. In this research, we have developed an intelligent, innovative and fully integrated multi agent model, which is used for vehicle-to-vehicle communications. The developed model is supported by an intelligent system based on a Nonlinear External Neural Network (NARX) and signal estimation theory. The system is built using real vehicles sensors, Arduino, GSM and RF technologies. The system is tested by applying different scenarios and observing vehicle behaviors. The results show that the smart system is able to make the appropriate decision based on both the vehicle's current condition and sensor readings. The developed system is able to operate effectively in a noisy environment in an excellent manner.

scholarly journals Hybrid Strategy for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks

2021 ◽  
Author(s):  
Karcius Assis ◽  
Alex Santos ◽  
Raul Almeida ◽  
Thiale Moura ◽  
Rafael Vieira ◽  
...  
Keyword(s):  
Optical Networks ◽  
Assignment Problem ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Modulation Formats ◽  
Hybrid Strategy ◽  
Spectrum Assignment ◽  
Modulation Format ◽  
Alternative Routing ◽  
Run Time

Abstract In this paper, we propose a novel hybrid strategy that combines mixed integer linearprogramming (MILP) formulation with different alternative routing approaches that is capable ofsolving, simultaneously, the routing, modulation format and spectrum assignment problem in thedesign of elastic optical networks. We extend our proposal to a path-link formulation that, althoughit is not guaranteed to find the optimal solution, it has shown reasonable solutions within inferiorsimulation time, allowing it to be used in not very short networks. We also compare our proposalwith another MILP formulation and three adapted heuristics, all available in the literature. Theresults show the benefits of our proposal considering diverse simulation scenarios and differentnumber of modulation formats over19realistic networks in terms of simulation run time andmaximum number of used set of slots.

scholarly journals Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

2021 ◽  
Vol 11 (22) ◽  
pp. 10547
Author(s):  
Marios Gatzianas ◽  
Agapi Mesodiakaki ◽  
George Kalfas ◽  
Nikos Pleros ◽  
Francesca Moscatelli ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Network Function Virtualization ◽  
User Association ◽  
Computational Resource ◽  
Mixed Integer Linear Program ◽  
Resource Allocation Algorithm ◽  
Network Function

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.

scholarly journals A Model-Based Optimisation Approach for Process Synthesis of Olefins from Petroleum with Application to the Malaysian Petrochemical Industry

2019 ◽  
Vol 12 ◽  
pp. 1-15
Author(s):  
Khor Cheng Seong
Keyword(s):  
Practical Knowledge ◽  
Optimal Solution ◽  
Raw Material ◽  
Mixed Integer ◽  
Hydrocarbon Mixture ◽  
Continuous Variables ◽  
Mixed Integer Linear Program ◽  
Actual Case ◽  
Model Based ◽  
Recent Developments

The shale gas revolution has rekindled interest in olefins production due to the abundance of ethane as a raw material resource. However, the main technology still revolves around the cost-intensive distillation operation. Hence this work aims to investigate the economic optimisation of olefins synthesis from petroleum in the light of recent developments. A model-based approach is applied to determine the optimal sequencing of separation and reaction processes for a multi-component hydrocarbon mixture feed to produce mainly ethylene and propylene. a mixed-integer linear program (MILP) is formulated based on a superstructure that captures numerous plausible synthesis alternatives. The model comprises linear mass balance reactor representation and simple sharp distillation based on split fractions for product recovery. Integer binary variablesis used for selecting the task for equipment and continuous variables for representing the flowrate of each task. To expedite converging to an optimal solution of a least total annualised cost configuration, the formulation is appended with logical constraints on the design and structural specifications derived from heuristics based on practical knowledge and experience. The modelling approach on actual case studies based on two such petrochemical facilities operating in Malaysia is implemented. Additionally, the solution analysis is enriched with the investigation on a second- and third-best (suboptimal) configurations obtained through appropriate integer cuts as constraints to the model. The results show good agreement with existing plant configurations, thus substantiating the value and verification of the proposed model-based optimisation approach.

scholarly journals HADES: A Multi-Agent Platform to Reduce Congestion Anchoring Based on Temporal Coordination of Vessel Arrivals—Application to the Multi-Client Liquid Bulk Terminal in the Port of Cartagena (Spain)

2021 ◽  
Vol 11 (7) ◽  
pp. 3109
Author(s):  
Pilar Jiménez ◽  
José María Gómez-Fuster ◽  
Pablo Pavón-Mariño
Keyword(s):  
Mixed Integer ◽  
Berth Allocation ◽  
Limited Information ◽  
Key Factors ◽  
Berth Allocation Problem ◽  
Mixed Integer Linear Program ◽  
Agent Platform ◽  
Liquid Bulk ◽  
Multi Agent ◽  
Time Changes

Ports are key factors in international trade, and new port terminals are quite costly and time consuming to build. Therefore, it is necessary to optimize existing infrastructure to achieve sustainability in logistics. This problem is more complex in multi-client port terminals, where quay infrastructure is shared among terminal operators who often have conflicting interests. Moreover, the berth allocation problem in liquid bulk terminals implies demanding restrictions due to the reduced flexibility in berth allocation for these types of goods. In this context, this paper presents HADES, a multi-agent platform, and the experience of its pilot use in the Port of Cartagena. HADES is a software platform where agents involved in vessel arrivals share meaningful but limited information. This is done to alleviate potential congestion in multi-client liquid bulk terminals, promoting a consensus where overall congestion anchoring is reduced. A study is presented using a mixed integer linear program (MILP) optimization model to analyze the maximum theoretical reduction in congestion anchoring, depending on the flexibility of vessel arrival time changes. Results show that 6 h of flexibility is enough to reduce congestion anchoring by half, and 24 h reduces it to negligible values. This confirms the utility of HADES, which is also briefly described.

scholarly journals An Optimal Transportation Schedule of Mobile Equipment

2012 ◽  
Vol 10 (5) ◽  
Author(s):  
S. Guillén-Burguete ◽  
H. Sánchez-Larios ◽  
J.G Vázquez-Vázquez
Keyword(s):  
Optimal Solution ◽  
Road Construction ◽  
Transportation Cost ◽  
Convex Polyhedra ◽  
Mixed Integer ◽  
Time Intervals ◽  
Mixed Integer Linear Program ◽  
Arrival Times ◽  
Indefinite Number ◽  
Total Transportation Cost

Motivated by a problem faced by road construction companies, we develop a new model to obtain an optimaltransportation schedule of mobile machines which have to travel to execute tasks. In this problem, each task ischaracterized by the location where it is to be executed, a work-content in terms of machine-time units, and one ormore time intervals within which it can be performed. The machines can be transported from one location to anotherat any time, thus the problem has an indefinite number of variables. However, this indefinite number of variables canbe reduced to a definite one because, as we prove, the problem has an optimal solution in which the arrivals ofmachines occur only at certain time instants. The objective is to minimize the total transportation cost such that all thetasks are executed within their time intervals. The constraints ensuring that the tasks are processed within theirprescribed time intervals are nonlinear; nevertheless, due to the sets of the possible arrival times of the machinesforming bounded convex polyhedra, our problem can be transformed into a mixed integer linear program by the samedevice used in the decomposition principle of Dantzig-Wolfe.

scholarly journals Optimization flow model for handling car flows at the marshalling yard

2018 ◽  
Vol 216 ◽  
pp. 02024
Author(s):  
Alexander Alexandrov ◽  
Alexander Galkin ◽  
Elena Timukhina ◽  
Nikolai Tushin
Keyword(s):  
Process Model ◽  
Heuristic Algorithms ◽  
Complex Structure ◽  
Optimal Solution ◽  
Operational Planning ◽  
Mixed Integer ◽  
Railway Transport ◽  
Mixed Integer Linear Program ◽  
Marshalling Yard

Mathematical modeling is widely used in studies of operational planning in railway transport. Mainly heuristic algorithms and simulation modeling is used in short-term planning at marshalling yards. There is an opportunity to improve the quality of planning using strict optimization models. The objective of the study was to find a way to optimize the multi-terminal transport flows of the complex structure by the example of operational planning for handling car flows at the marshalling yard. The process model was built on the basis of Mixed Integer Linear Program (MILP) method. The article provides the mathematical setting and describes results of calculations of the reference example. The LpSolve application package was used. The technological effect is estimated through checking the optimal solution on the simulation model.

Optimal Operational Planning of Utility Systems in Petrochemical Plants Using an Improved Particle Swarm Optimization Algorithm

2010 ◽  
Vol 143-144 ◽  
pp. 1364-1369
Author(s):  
Wen Zhi Dai ◽  
Zhao Yi Huo ◽  
Hong Chao Yin ◽  
Hai Feng Liang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Mixed Integer Linear Program ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Utility Systems ◽  
New Algorithms

In this paper, the operation optimization problem for utility systems is formulated and a mixed integer linear program (MILP) model is presented. The objective function of the model is to minimize the operational cost of utility systems during the whole operational period. In order to obtain the optimal solution of the foregoing model, an improved particle swarm optimization is proposed. Finally, a case with quantitive results presented is considered for illustrating the advantage of proposed optimization approach. Results show that the new algorithms are much more efficient than some existing particle swarm optimization algorithms.

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