Essec\Faculty\Model\Contribution {#2233 ▼
#_index: "academ_contributions"
#_id: "15394"
#_source: array:26 [
"id" => "15394"
"slug" => "15394-stochastic-scheduling-and-routing-decisions-in-online-meal-delivery-platforms-with-mixed-force"
"yearMonth" => "2025-05"
"year" => "2025"
"title" => "Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force"
"description" => "ZHAO, Y., ALFANDARI, L. et ARCHETTI, C. (2025). Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force. <i>European Journal of Operational Research</i>, 323(1), pp. 139-152. 
ZHAO, Y., ALFANDARI, L. et ARCHETTI, C. (2025). Stochastic scheduling and routing decisions in onlin "
"authors" => array:3 [
0 => array:3 [
"name" => "ALFANDARI Laurent"
"bid" => "B00000901"
"slug" => "alfandari-laurent"
]
1 => array:1 [
"name" => "Zhao Yanlu"
]
2 => array:1 [
"name" => "Archetti Claudia"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Routing"
1 => "Online meal delivery"
2 => "Scheduling and routing decisions"
3 => "Mixed delivery force"
4 => "Markov decision process"
]
"updatedAt" => "2025-03-26 11:05:22"
"publicationUrl" => "https://doi.org/10.1016/j.ejor.2024.11.028"
"publicationInfo" => array:3 [
"pages" => "139-152"
"volume" => "323"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) service. The huge increase in meal delivery demand requires the service providers to construct a highly efficient logistics network to deal with a large-volume of time-sensitive and fluctuating fulfillment, often using inhouse and crowdsourced drivers to secure the ambitious service quality. We aim to address the problem of developing an effective scheduling and routing policy that can handle real-life situations. To this end, we first model the dynamic problem as a Markov Decision Process (MDP) and analyze the structural properties of the optimal policy. Then we propose four integrated approaches to solve the operational level scheduling and routing problem. In addition, we provide a continuous approximation formula to estimate the bounds of required fleet size for the inhouse drivers. Numerical experiments based on a real dataset show the effectiveness of the proposed solution approaches. We also obtain several managerial insights that can help decision makers in solving similar resource allocation problems in real-time. This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) "
"en" => "This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) service. The huge increase in meal delivery demand requires the service providers to construct a highly efficient logistics network to deal with a large-volume of time-sensitive and fluctuating fulfillment, often using inhouse and crowdsourced drivers to secure the ambitious service quality. We aim to address the problem of developing an effective scheduling and routing policy that can handle real-life situations. To this end, we first model the dynamic problem as a Markov Decision Process (MDP) and analyze the structural properties of the optimal policy. Then we propose four integrated approaches to solve the operational level scheduling and routing problem. In addition, we provide a continuous approximation formula to estimate the bounds of required fleet size for the inhouse drivers. Numerical experiments based on a real dataset show the effectiveness of the proposed solution approaches. We also obtain several managerial insights that can help decision makers in solving similar resource allocation problems in real-time. This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) "
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2025-04-06T00:21:40.000Z"
"docTitle" => "Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force"
"docSurtitle" => "Articles"
"authorNames" => "<a href="/cv/alfandari-laurent">ALFANDARI Laurent</a>, Zhao Yanlu, Archetti Claudia"
"docDescription" => "<span class="document-property-authors">ALFANDARI Laurent, Zhao Yanlu, Archetti Claudia</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2025</span> <span class="document-property-authors">ALFANDARI Laurent, Zhao Yanlu, Archetti Claudia</span><br><s "
"keywordList" => "<a href="#">Routing</a>, <a href="#">Online meal delivery</a>, <a href="#">Scheduling and routing decisions</a>, <a href="#">Mixed delivery force</a>, <a href="#">Markov decision process</a> <a href="#">Routing</a>, <a href="#">Online meal delivery</a>, <a href="#">Scheduling and routing de "
"docPreview" => "<b>Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force</b><br><span>2025-05 | Articles </span> <b>Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force</b "
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.1016/j.ejor.2024.11.028" target="_blank">Stochastic scheduling and routing decisions in online meal delivery platforms with mixed force</a> <a href="https://doi.org/10.1016/j.ejor.2024.11.028" target="_blank">Stochastic scheduling and routi "
]
+lang: "fr"
+"_type": "_doc"
+"_score": 8.678904
+"parent": null
}
