A Game-Theoretic Approach to Share the Costs of Cooperating Healthcare Networks

The growing demand for healthcare services combined with the disarray in the health insurance market in the United States has created a situation where rival health networks are aggressively competing by building duplicate health facilities and providing redundant services in localized geographic regions. Unfortunately, this strategy can reduce the quality of patient care and decrease profits (Kaissi & Charland, 2013). A solution to this problem is for health networks to cooperate and share healthcare equipment, facilities, and personnel. Toward that end, this paper presents a game-theoretic method that can share these costs in a fair, efficient, and repeatable manner

A machine learning approach for allocating route cost to customers for transportation and logistics services.

Advancements in big data enabled management practices inspire logistics companies to study deeper into their transportation operations with a data driven approach. One such question asks: How can a logistics firm identify high-cost customers in their service network? In the presence of rich data on routes involving many customers, this thesis develops a framework to allocate a route cost among customers that the route serves, where each route is associated with multiple route features related to the transportation cost. Cost is allocated using the proportional allocation approach in combination with the random forest method in machine learning. First, this framework ensembles random forest regression models to determine the importance values of all route features. Next, the importance values of route features are used to allocate cost among customers. Finally, posterior analysis identifies customers in a route or in general that are most costly to serve. Several additional analyses are performed to show potential uses of this cost allocation output. Results of the framework and analyses on three simulated case and two industry cases show the validity of the model and the potential for actionable operational analysis and changes

Estimation and Allocation of Cost Savings from Collaborations

학위논문(석사) -- 서울대학교대학원 : 공과대학 산업공학과, 2021.8. 문일경.The physical internet (PI) is a state-of-the-art open global supply chain network that is gaining attention from both participants and researchers of supply chains. The PI uses standardized containers to dispatch shipments through an interconnected network within a supply chain, where information, storage facilities, and transportation methods are shared participants of the physical internet. The network aims to save costs, handle volatile demand and information, and be socially and environmentally responsible. Up until now, however, almost all studies concerning the PI have focused primarily on its conceptual development and the advantages of putting it into practical, widespread use. Studies that consider realistic constraints of its use, such as empty runs of transportation, limited capacity of resources, or an equitable allocation of the cost savings obtained from its implementation are limited. While in general the PI can offer greater efficiency and sustainability compared to the traditional supply chain network, in certain situations some users of it experience loss through its use because of the inherent setup it presents of sharing capacitated resources. Therefore, compensating companies that experience loss when joining a PI is essential in building a solid network. In this thesis, in order to address the minimization of a total cost problem in the production-inventory-distribution decision of a PI, we first propose a mixed-integer linear programming (MILP) model formulation that takes into account capacitated factory and warehouse capacity, the penalty sustained by empty runs of transportation, and the maximum delivery distance of freight runs. Next, we use the model to compare the costs incurred by individual players when they do not participate in the PI and the costs of collaboration in the PI in which players do participate. After comparing the costs saved by participating in the PI, we then allocated the cost savings among independent supply chains, allotting them through three different allocation methods, including the Shapley value method, which is a cooperative game theory solution method.피지컬 인터넷은 최첨단의 공유 글로벌 공급망 네트워크로 다양한 학자 및 실무자들의 관심을 끌고 있습니다. 피지컬 인터넷은 표준화된 컨테이너를 이용하여 상호 연결된 네트워크를 통해 제품 및 재화를 발송합니다. 이 때, 정보, 보관 시설 및 운송 수단은 참여자들 간에 공유됩니다. 이 네트워크는 비용을 절감하고 변동성이 큰 수요와 정보를 처리하고 사회적, 환경적으로 지속가능성을 유지하는 것을 목표로 합니다. 지금까지 피지컬 인터넷에 대한 연구는 주로 그 개념과 프레임워크의 개발, 그리고 사회에 도입하였을 때의 장점을 주로 다루었습니다. 피지컬 인터넷 속에서 운송 수단의 공차 운행, 자원의 한계 용량, 절감한 비용의 배분 등과 같은 현실적인 요소들에 대한 고려를 한 연구들은 아직 제한적입니다. 피지컬 인터넷은 전체적으로 보았을 때 기존의 공급망에 비해 더 큰 효율성과 지속 가능성을 얻을 수 있지만 특정한 상황에서는 일부 참가자는 현실적인 제약 상황으로 인해 오히려 손해를 보는 경우가 존재할 수 있습니다. 따라서 더 큰 효율성과 지속 가능성을 얻을 수 있는 피지컬 인터넷에 기업들을 참여시키기 위해선 그들이 참여함으로써 손해를 보는 상황을 만들지 않는 것이 필수적인 조건입니다. 본 논문에서는 먼저 운송 수단의 공차 운행 페널티 비용, 최대 운송 가능 거리, 창고의 폐쇄를 고려한 통합 생산-재고-물류 최소 비용 혼합 정수 선형 계획법 모형을 제안하였습니다. 그 후, 개별적인 공급망의 비용과 피지컬 인터넷 하에서 협업한 통합 공급망의 비용을 비교하여 비용 절감 효과를 계산한 후 협력 게임의 일종인 섀플리 값을 포함한 세 가지 배분 방법을 통해 비용 절감 효과 배분을 살펴보았습니다.Chapter 1 Introduction 1 Chapter 2 Literature Review 5 2.1 The Physical Internet 5 2.2 Cost Savings Allocation Problem 8 Chapter 3 Model Formulation 10 3.1 Problem Definition 10 3.2 Assumptions 15 3.3 Notaions and Formulations 17 Chapter 4 Numerical Analysis of the MILP model 22 4.1 Experimental Design 22 4.2 Results Analysis 26 4.3 Cost Parameter Sensitivity Analysis 29 Chapter 5 Cost Savings Allocation Problem 31 5.1 No Pre-set Rules 31 5.2 Proportional to Customer Demand 33 5.3 The Shapley Value 35 Chapter 6 Conclusions 37 Bibliography 39 국문초록 42석

Integrating partner objectives in horizontal logistics optimisation models

In this paper a general solution framework is presented for optimising decisions in a horizontal logistics cooperation. The framework distinguishes between the objective of the group and the objectives of the individual partners in the coalition. Although the importance of the individual partner interests is often acknowledged in the literature, the proposed solution framework is the first to include these objectives directly into the objective function of the optimisation model. The solution framework is applied to a collaborative variant of the clustered vehicle routing problem, for which we also create a set of benchmark instances. We find that by only considering a global coalition objective, the obtained solution is often suboptimal for some partners in the coalition. Providing a set of high quality alternative solutions that are Pareto efficient with respect to the partner objectives, gives additional insight in the sensitivity of a solution, which can support the decision making process. Our computational results therefore acknowledge the importance of including the individual partner objectives into the optimisation procedure

Roteirização colaborativa de veículos: aplicação na logística militar / Collaborative Vehicle Routing: Application In Military Logistics

Diante de um cenário em que cada Força Armada planeja e executa seus transportes individuais, a inserção da roteirização colaborativa nos planejamentos militares visa compartilhar de veículos Forças a fim de minimizar a distância total percorrida. Este artigo foi usado um modelo unificado de roteirização de veículos que emprega uma metaheurística de busca adaptativa em grande vizinhança para atingir os resultados de roteirização colaborativa com clientes compartilhados. A contribuição artigo está na apresentação de uma metodologia de três fases para a solução de um problema de roteirização com clientes compartilhados usando os problemas de roteirização com um e com múltiplos depósitos. Realizou-se um estudo de caso para roteirização da distribuição de suprimentos militares da Marinha, do Exército e da Aeronáutica

Co-distribución para logística urbana: análisis de experiencias internacionales

Population growth has been accompanied by an increase in the percentage of people living in urban centers in both developed and non-developed countries. These areas with high population density generate an increase in commercial activity, with urban freight transport being a key factor, as it provides the products marketed by its stores. However, market capillarity, strict time windows and lack of infrastructure cause this activity to be carried out inefficiently and therefore, at a high cost. Moreover, urban freight transportation affects other externalities such as contamination, noise and existing traffic congestion. Several authors have proposed co-distribution as a way to improve the distribution system and mitigate the problems mentioned above. This article aims to gather and analyze information on the different methods used in co-distribution in different parts of the world, supported by practical experiences. As a result, it is concluded that almost all articles published in this subject refer to the implementation of Urban Consolidation Centers, which, while mitigating several of the problems mentioned, they generally need support from the government to make them economically viable.El crecimiento en la población ha sido acompañado por un aumento en el porcentaje de las personas que habitan los centros urbanos, tanto en países desarrollados como no desarrollados. Estas zonas con alta densidad de población generan un aumento en la actividad comercial, siendo el transporte urbano de mercaderías un factor clave, ya que provee los productos comercializados por sus tiendas. Sin embargo, la capilaridad del mercado, estrictas ventanas horarias y falta de infraestructura provocan que esta actividad se realice de manera ineficiente y por lo tanto, a un costo elevado. Por otro lado, el transporte de mercaderías afecta otras externalidades como la contaminación, el ruido y la congestión de tránsito ya existente. Varios autores han investigado la co-distribución como una forma de mejorar el sistema de distribución urbana y mitigar los problemas anteriormente mencionados. Este artículo pretende recopilar y analizar la información sobre los diferentes métodos utilizados en co-distribución a nivel mundial con sustento en experiencias prácticas. Como resultado, se concluye que casi la totalidad de los artículos publicados en esta temática refieren a la implementación de Centros de Consolidación Urbanos (CCU), los cuales, si bien mitigan varios de los problemas mencionados, en general necesitan de apoyo por parte del gobierno para que sean económicamente viables

Balancing partner preferences for logistics costs and carbon footprint in a horizontal cooperation

Horizontal cooperation in logistics has gathered momentum in the last decade as a way to reach economic as well as environmental benefits. In the literature, these benefits are most often assessed through aggregation of demand and supply chain optimization of the partnership as a whole. However, such an approach ignores the individual preferences of the participating companies and forces them to agree on a unique coalition objective. Companies with different (potentially conflicting) preferences could improve their individual outcome by diverging from this joint solution. To account for companies preferences, we propose an optimization framework that integrates the individual partners’ interests directly in a cooperative model. The partners specify their preferences regarding the decrease of logistical costs versus reduced CO2 emissions. Doing so, all stakeholders are more likely to accept the solution, and the long-term viability of the collaboration is improved. First, we formulate a multi-objective, multi-partner location-inventory model. Second, we distinguish two approaches for solving it, each focusing primarily on one of these two dimensions. The result is a set of Pareto-optimal solutions that support the decision and negotiation process. Third, we propose and compare three different approaches to construct a unique solution which is fair and efficient for the coalition. Extensive numerical results not only confirm the potential of collaboration but, more importantly, also reveal valuable managerial insights on the effect of dissimilarities between partners with respect to size, geographical overlap and operational preferences