Allocation in Practice

How do we allocate scarcere sources? How do we fairly allocate costs? These are two pressing challenges facing society today. I discuss two recent projects at NICTA concerning resource and cost allocation. In the first, we have been working with FoodBank Local, a social startup working in collaboration with food bank charities around the world to optimise the logistics of collecting and distributing donated food. Before we can distribute this food, we must decide how to allocate it to different charities and food kitchens. This gives rise to a fair division problem with several new dimensions, rarely considered in the literature. In the second, we have been looking at cost allocation within the distribution network of a large multinational company. This also has several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on Artificial Intelligence (KI 2014), Springer LNC

A statistical comparison of two safety stock replenishment mechanisms in a cyclic stochastic IRP

Preventing stock-out in a replenishment system, in which customer demand rates are stochastic with constant averages, can be accomplished via safety stocks hold at each customer. These safety stocks should be replenished back to their initial levels each time they are used. However, sometimes it occurs that a truck does not have enough capacity to carry the amount of the product the visited customers need to restore their stocks and safety stocks to their required levels. Therefore, the carried extra amount of the product, intended to replenish safety stocks, should be divided amongst the customers in some optimal or fair manner. To achieve this fair allocation, we propose and analyze two policies, the first called Fair-share and the second Ratio methods. Details on how these two methods are implemented, to achieve the level of service expected at each customer, are discussed and illustrated. In addition a simulation model is developed and used to compare the performance of each policy in the long run

Two-echelon freight transport optimisation: unifying concepts via a systematic review

Multi-echelon distribution schemes are one of the most common strategies adopted by the transport companies in an aim of cost reduction, but their identification in scientific literature is not always easy due to a lack of unification. This paper presents the main concepts of two-echelon distribution via a systematic review, in the specific a meta-narrative analysis, in order to identify and unify the main concepts, issues and methods that can be helpful for scientists and transport practitioners. The problem of system cost optimisation in two-echelon freight transport systems is defined. Moreover, the main variants are synthetically presented and discussed. Finally, future research directions are proposed.location-routing problems, multi-echelon distribution, cross-docking, combinatorial optimisation, systematic review.

Freight distribution systems with cross-docking: a multidisciplinary analysis

Freight transport constitutes one of the main activities that influences economy and society, as it assures a vital link between suppliers and customers and it represents a major source of employment. Multi-echelon distribution is one of the most common strategies adopted by the transport companies in an aim of cost reduction. This paper presents the main concepts of multi-echelon distribution with cross-docks through a multidisciplinary analysis that includes an optimisation study (using both exact and heuristic methods), a geographic approach (based on the concept of accessibility) and a socio-economic analysis. a conceptual framework for logistics and transport pooling systems, as well as a simulation method for strategic planning optimisation.Freight transport systems, cross-docking, simulation, collaboration, socio-economic issues

Optimizing the inventorying and distribution of chemical fluids: An innovative nested column generation approach

Vendor-managed-inventory is a successful business practices based on the cooperation between a supplier and its customers in which demand and inventory information from the customers are shared with the supplier. This practice is gaining popularity in the chemical industry and relies on the inventory-routing-problem, which integrates inventory management, vehicle routing, and delivery scheduling decisions. This one is a difficult combinatorial optimization problem both theoretically and practically. However, because of the large expenses involved in distribution and inventorying of chemical products, it is attractive to make use of optimization tools for exploiting as many degrees of freedom as possible with the goal of minimizing both distribution and inventorying costs. Consequently, we propose a nested column generation algorithm for solving an inventorying and distribution problem that models the delivery of several chemicals fluids. The approach is building on a column generation & incomplete branch-and-price algorithm in which for each delivery route, the delivery patterns of fluids are also determined by column generation. We detail the implementation and provide computational results for realistic test instances.Fil: Coccola, Mariana Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

Considering inventory distributions in a stochastic periodic inventory routing system

Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers have proposed the usage of safety stock to avoid stock-out. However, finding the precise level of safety stock depends on forecasting the statistical distribution of demand rates and their variations in different settings among the planning horizon. In this paper the demand rate distributions and its parameters are taken into account for each time period in a stochastic periodic IRP. An analysis of the achieved statistical distribution of the inventory and safety stock level is provided to measure the effects of input parameters on the output indicators. Different values for coefficient of variation are applied to the customers’ demand rate in the optimization model. The outcome of the deterministic equivalent model of SPIRP is simulated in form of an illustrative case

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

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed