A Decision Support Tool for the Location Routing Problem During the COVID-19 Outbreak in Colombia

2021 ◽  
pp. 33-46
Author(s):  
Andrés Martínez-Reyes ◽  
Carlos L. Quintero-Araújo ◽  
Elyn L. Solano-Charris
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Support Tool ◽  
Location Routing

A decision-support tool for a capacitated location-routing problem

2008 ◽  
Vol 46 (1) ◽  
pp. 366-375 ◽  
Author(s):  
Rui Borges Lopes ◽  
Sérgio Barreto ◽  
Carlos Ferreira ◽  
Beatriz Sousa Santos
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Support Tool ◽  
Location Routing ◽  
Capacitated Location

Interactive Spatial Decision-Support System for Multiobjective Hazardous Materials Location-Routing Problems

1997 ◽  
Vol 1602 (1) ◽  
pp. 101-109 ◽  
Author(s):  
João Coutinho-Rodrigues ◽  
John Current ◽  
João Climaco ◽  
Samuel Ratick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Hazardous Materials ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Selection Of

Hazardous materials (hazmat) logistics management has received increased attention in the past two decades. Important decisions in such management include the selection of sites for hazmat processing and storage, the selection of transportation routes from sources to processing facilities, and the determination of quantities of hazmat shipped over these routes. These decisions are frequently based on multiple criteria (e.g., cost, risk, equity). A personal computer–based, interactive spatial decision-support system was designed to assist decision makers with such problems. Although presented within the framework of a hazmat problem, the system’s components can be modified to analyse any multiobjective location, routing, or location-routing problem.

scholarly journals A heuristic approach for green vehicle routing

2020 ◽  
Author(s):  
MEHMET SOYSAL ◽  
Mustafa Çimen ◽  
Çağrı Sel ◽  
Sedat Belbağ
Keyword(s):  
Dynamic Programming ◽  
Decision Support ◽  
Vehicle Routing ◽  
Decision Support Tool ◽  
Programming Approach ◽  
Base Case ◽  
Routing Problem ◽  
Support Tool ◽  
Solution Approach ◽  
Sustainable Logistics

This paper addresses a green capacitated vehicle routing problem that accounts for transportation emissions. A Dynamic Programming approach has been used to formulate the problem. Although small-sized problems can be solved by Dynamic Programming, this approach is infeasible for larger problems due to the curse of dimensionality. Therefore, we propose a Dynamic Programming based solution approach that involves the ideas of restriction, simulation and online control of parameters to solve large-sized problems. The added values of the proposed decision support tool have been shown on a small-sized base case and relatively larger problems. Performance comparisons of the proposed heuristic against other existing Dynamic Programming based solution approaches reveal its effectiveness, as in most of the instance-setting pairs, the proposed heuristic outperforms the existing ones. Accordingly, the proposed heuristic can be used as an alternative decision support tool to tackle real routing problems confronted in sustainable logistics management.

scholarly journals Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem

2021 ◽  
Vol 13 (14) ◽  
pp. 7822
Author(s):  
Andrés Martínez-Reyes ◽  
Carlos L. Quintero-Araújo ◽  
Elyn L. Solano-Charris
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Personal Protective Equipment ◽  
Demand Uncertainty ◽  
Medical Personnel ◽  
Protective Equipment ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Support Tool ◽  
Location Routing

The coronavirus disease 2019, known as COVID-19, has generated an imminent necessity for personal protective equipment (PPE) that became essential for all populations and much more for health centers, clinics, hospitals, and intensive care units (ICUs). Considering this fact, one of the main issues for cities’ governments is the distribution of PPE to ICUs to ensure the protection of medical personnel and, therefore, the sustainability of the health system. Aware of this challenge, in this paper, we propose a simheuristic approach for supplying personal protective equipment to intensive care units which is based on the location-routing problem (LRP). The objective is to provide decision makers with a decision support tool that considers uncertain demands, distribution cost, and reliability in the solutions. To validate our approach, a case study in Bogotá, Colombia was analyzed. Computational results show the efficiency of the usage of alternative safety stock policies to face demand uncertainty in terms of both expected stochastic costs and reliabilities.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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