A hybrid approach to solve the dynamic patrol routing problem for group of underwater robots

PurposeFinding a rational approach to maintain a freshness of foods and perishable goods and saving their intrinsic attributes during a distribution of these products is one of the main issues for distribution and logistics companies. This paper aims to provide a framework for distribution of perishable goods which can be applied for real life situations.Design/methodology/approachThis paper proposes a novel mathematical model for transportation inventory location routing problem. In addition, the paper addresses the impact of perishable goods age on the demand of final customers. The model is optimally solved for small- and medium-scale problems. Moreover, regarding to NP-hard nature of the proposed model, two simple and one hybrid metaheuristic algorithms are developed to cope with the complexity of problem in large scale problems.FindingsNumerical examples with different scenarios and sensitivity analysis are conducted to investigate the performance of proposed algorithms and impacts of important parameters on optimal solutions. The results show the acceptable performance of proposed algorithms.Originality/valueThe authors formulate a novel mathematical model which can be applicable in perishable goods distribution systems In this regard, the authors consider lost sale which is proportional to age of products. A new hybrid approach is applied to tackle the problem and the results show the rational performance of the algorithm.

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Solving Multi-Objective Multicast Routing Problem Using a New Hybrid Approach

International Journal of Applied Evolutionary Computation ◽

10.4018/ijaec.2018100102 ◽

2018 ◽

Vol 9 (4) ◽

pp. 22-36

Author(s):

Mohammed Mahseur ◽

Abdelmadjid Boukra ◽

Yassine Meraihi

Keyword(s):

Multicast Routing ◽

Hybrid Approach ◽

Bat Algorithm ◽

Pareto Optimal Solutions ◽

Optimal Solutions ◽

Routing Problem ◽

Multi Objective ◽

Strength Pareto Evolutionary Algorithm ◽

Quality Of Service Parameters

Multicast routing is the problem of finding the spanning tree of a set of destinations whose roots are the source node and its leaves are the set of destination nodes by optimizing a set of quality of service parameters and satisfying a set of transmission constraints. This article proposes a new hybrid multicast algorithm called Hybrid Multi-objective Multicast Algorithm (HMMA) based on the Strength Pareto Evolutionary Algorithm (SPEA) to evaluate and classify the population in dominated solutions and non-dominated solutions. Dominated solutions are evolved by the Bat Algorithm, and non-dominated solutions are evolved by the Firefly Algorithm. Old and weak solutions are replaced by new random solutions by a process of mutation. The simulation results demonstrate that the proposed algorithm is able to find good Pareto optimal solutions compared to other algorithms.

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A Branch-and-Price Framework for the Maximum Covering and Patrol Routing Problem

Lecture Notes in Management and Industrial Engineering - Data and Decision Sciences in Action 2 ◽

10.1007/978-3-030-60135-5_5 ◽

2021 ◽

pp. 59-80

Author(s):

Paul A. Chircop ◽

Timothy J. Surendonk ◽

Menkes H. L. van den Briel ◽

Toby Walsh

Keyword(s):

Branch And Price ◽

Routing Problem ◽

Patrol Routing

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Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem

International Journal of Production Economics ◽

10.1016/j.ijpe.2015.03.021 ◽

2015 ◽

Vol 170 ◽

pp. 805-814 ◽

Cited By ~ 49

Author(s):

Chen-Yang Cheng ◽

Yin-Yann Chen ◽

Tzu-Li Chen ◽

John Jung-Woon Yoo

Keyword(s):

Particle Swarm Optimization ◽

Ant Colony Optimization ◽

Hybrid Approach ◽

Particle Swarm ◽

Ant Colony ◽

Swarm Optimization ◽

Routing Problem ◽

Order Batching

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A Hybrid Approach to Solve the Vehicle Routing Problem with Time Windows and Synchronized Visits In-Home Health Care

Arabian Journal for Science and Engineering ◽

10.1007/s13369-020-04828-5 ◽

2020 ◽

Vol 45 (12) ◽

pp. 10637-10652

Author(s):

Jalel Euchi ◽

Salah Zidi ◽

Lamri Laouamer

Keyword(s):

Health Care ◽

Vehicle Routing ◽

Home Health Care ◽

Vehicle Routing Problem ◽

Time Windows ◽

Hybrid Approach ◽

Home Health ◽

Routing Problem

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Applied BIM: AMT and MTSP Integrated Approach for the Interior Patrol Routing Problem

Computing in Civil Engineering 2017 ◽

10.1061/9780784480823.010 ◽

2017 ◽

Author(s):

Chun-Hao Chen ◽

Albert Y. Chen

Keyword(s):

Integrated Approach ◽

Routing Problem ◽

Patrol Routing

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Analysing the Police Patrol Routing Problem: A Review

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9030157 ◽

2020 ◽

Vol 9 (3) ◽

pp. 157 ◽

Cited By ~ 2

Author(s):

Maite Dewinter ◽

Christophe Vandeviver ◽

Tom Vander Beken ◽

Frank Witlox

Keyword(s):

Police Officers ◽

Keyword Search ◽

Hybrid Genetic Algorithm ◽

Dynamic Vehicle Routing ◽

Routing Problem ◽

Police Patrol ◽

Starting Point ◽

Solution Methods ◽

Routing Policies ◽

Patrol Routing

Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP.

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