A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations

Maliki, Fouad; Souier, Mehdi; Dahane, Mohammed; Abdelaziz, Fouad Ben

doi:10.1007/s10479-022-04945-4

Cited by 8 publications

(3 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang et al [37] also considered the multiperiod aspect in their drone-based robust vaccination location and scheduling model that optimises the facilities to open throughout the time horizon, the number of drones to deploy and the number of vaccines to administer at each period. Maliki et al [38] also developed a multi-period facility location model but using mobile facilities. They considered demand fluctuations and facility disruptions at each period and optimised locations and assignments while balancing the total costs and CO 2 emissions.…”

Section: Location Problemsmentioning

confidence: 99%

Multiperiod vaccination facility planning

Tacadao,

Simonis,

Quesada

et al. 2024

Preprint

View full text Add to dashboard Cite

We propose a decision support tool, based on Mixed Integer Programming, to help with the planning of national vaccination campaigns, and test it on data and scenarios obtained from the publicly available information about the Irish COVID-19 vaccination program. We show that a large variety of constraints can be included in the tool, as well as combinations of different objective functions for the different stakeholders. The tests show that the multi-period/multi-vaccine problem can be effectively solved by the given model, while allowing to consider the impact of potential changes in the input data. We also present a number of specific visualizations that help the user understand the plan created by the application.

show abstract

Section: Location Problemsmentioning

confidence: 99%

Multiperiod vaccination facility planning

Tacadao,

Simonis,

Quesada

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…They employed maximal coverage models with a focus on minimizing transportation time and travel distance. Maliki et al [26] studied multi-period FL decisions in scenarios emphasizing pandemics with volatile demand, and including opening, relocating, closing, and utilizing mobile facilities. They employed NSGA-II to balance economic costs and CO 2 emissions.…”

Section: Related Workmentioning

confidence: 99%

Test Center Location Problem: A Bi-Objective Model and Algorithms

Davoodi,

Calabrese

2024

Algorithms

View full text Add to dashboard Cite

The optimal placement of healthcare facilities, including the placement of diagnostic test centers, plays a pivotal role in ensuring efficient and equitable access to healthcare services. However, the emergence of unique complexities in the context of a pandemic, exemplified by the COVID-19 crisis, has necessitated the development of customized solutions. This paper introduces a bi-objective integer linear programming model designed to achieve two key objectives: minimizing average travel time for individuals visiting testing centers and maximizing an equitable workload distribution among testing centers. This problem is NP-hard and we propose a customized local search algorithm based on the Voronoi diagram. Additionally, we employ an ϵ-constraint approach, which leverages the Gurobi solver. We rigorously examine the effectiveness of the model and the algorithms through numerical experiments and demonstrate their capability to identify Pareto-optimal solutions. We show that while the Gurobi performs efficiently in small-size instances, our proposed algorithm outperforms it in large-size instances of the problem.

show abstract

“…These are mainly used when stochastic parameters exist in a SC network. Only a few studies adopted modelling and simulation techniques to study the complexities of SCRM (Maliki et al 2022;Tordecilla et al 2021). Scholars used different simulation techniques, such as Discrete-event simulation (DES), Agent-Based Simulation (ABS) or Multi-agent-based Simulation, System Dynamics (SD), Monte Carlo Simulation and Petri Nets based on the nature of the problems.…”

Section: Simulation-based Supply Chain Risk Modellingmentioning

confidence: 99%

Modelling and analysing supply chain disruption: a case of online grocery retailer

Mogale,

Wang,

Demir

et al. 2023

Oper Manag Res

View full text Add to dashboard Cite

Supply Chains (SCs) are becoming more vulnerable to disruption risks because of globalisation, competitiveness, and uncertainties. This study is motivated by an online grocery retailer in the UK that experienced multiple disruption risks, such as demand and supply shocks, facility closures, and disruption propagation simultaneously in 2020. The main purpose of this study is to model and perform quantitative analyses of a range of SC disruption risks affecting the UK online retailer. We have attempted to study how UK retailers responded to the first and second waves of the pandemic and the effect on multiple products. Six scenarios are developed based on SC disruption risks and their impacts on SC performance are analysed. The quantitative analysis of two strategies used by grocery retailers during the pandemic, namely vulnerable priority delivery slots and rationing of products, illustrates that rationing of products had a greater SC impact than the use of priority delivery slots. The effects of two resilience strategies, backup supplier and ramping up distribution centre capacity, are also quantified and discussed. Novel managerial insights and theoretical implications are discussed to make online grocery SC more resilient and robust during future disruptions.

show abstract

A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations

Cited by 8 publications

References 45 publications

Multiperiod vaccination facility planning

Multiperiod vaccination facility planning

Test Center Location Problem: A Bi-Objective Model and Algorithms

Modelling and analysing supply chain disruption: a case of online grocery retailer

Contact Info

Product

Resources

About