In the U.S., states are allowed to apply for the Affordable Care Act section 1332 waiver to explore innovative strategies in providing quality and affordable health insurance. Most approved waivers seek to establish state subsidized reinsurance programs, which help offset potential losses of high-cost enrollees in individual markets. State subsidized reinsurance programs are expected to reduce premiums

Buy-Now-Pay-Later (BNPL) service is one of the fastest-growing segments of financial technology in 2021. The BNPL program is a type of short-term finance that allows consumers to make purchases and pay for them interest-free over a predetermined brief period of time, usually weeks or months. In general, BNPL payment is instant-approval and no-credit-check right at checkout. As a result, BNPL payment

Making assortment decisions is becoming an increasingly difficult task for many retailers worldwide as they implement omnichannel initiatives. Discrete choice modeling lies at the core of this challenge, yet existing models do not sufficiently account for the complex shopping behavior of customers in an omnichannel environment. In this paper, we introduce a discrete choice model called the multichannel

In industry, production is often organized in the form of a hybrid flow shop, and there is great interest in methods and algorithms for optimizing such production processes. While, thus far, methods have focused mostly on optimizing a single selected objective, it is increasingly important to address several objectives simultaneously in order to move from extreme to balanced solutions that consider

After the closure of the schools in Hungary from March 2020 due to the pandemic, many students were left at home with no or not enough parental help for studying, and in the meantime some people had more free time and willingness to help others in need during the lockdown. In this paper we describe the optimisation aspects of a joint NGO project for allocating voluntary mentors to students using a

The paper focuses on investors whose strength of interest in sustainability issues (such as environmental, social, and governance) causes ESG to become a third criterion alongside risk and return in portfolio selection. This causes the efficient frontier to become an efficient surface. This means that an investor’s optimal portfolio is no longer the point of most preferred risk/return tradeoff on the

The area of maritime transportation optimization has recently begun to achieve increasing success at solving large scale models, and industry is steadily adopting operations research-based models and algorithms. However, the parameters of models in the maritime domain, like many others, are beset with uncertainty. The travel times of ships, the handling times at port, the amounts of demand available

In this paper, we propose a novel multivariate shortfall risk measure to evaluate the systemic risk of a financial system, where the allocation weight is scenario-dependent and optimally chosen from a predetermined feasible set, and examine its properties such as (quasi-)convexity and translation invariance. To compute the proposed risk measure, we reformulate it as a two-stage stochastic program.

The notion of a Bowley optimum has gained recent popularity as an equilibrium concept in problems of risk sharing and optimal reinsurance. In this paper, we examine the relationship between Bowley optimality and Pareto efficiency in a problem of optimal reinsurance, under fairly general preferences. Specifically, we show that Bowley-optimal contracts are indeed Pareto efficient but they make the insurer

In light of the existing practical applications of the two-dimensional loading on vehicle scheduling and many-to-many supply-demand relationships between suppliers and customers, we address a many-to-many heterogeneous vehicle routing problem with cross-docking and two-dimensional loading constraints (or the heterogeneous 2L-MVRPCD). The newly proposed problem can be regarded as a generalized problem

In this paper, we develop an integrated multitiered competitive agricultural supply chain network model in which agricultural firms and processing firms compete to sell their differentiated products. The focus here is on fresh produce and minimally processed such agricultural products, with quality also captured. The competition among agricultural firms and processing firms is studied through game

Determining optimal prices in non-convex markets remains an unsolved challenge. Non-convex costs are critical in electricity markets, as startup costs and minimum operating levels yield a non-convex optimal value function over demand levels. While past research largely focuses on the performance of different non-convex pricing frameworks in the short-run or uses convex approximations, we determine

This paper studies an interesting logistical problem related to maintaining a set of selected turbines in offshore wind farms. A service operation vessel (SOV), used to support maintenance activities, also carries a safe transfer boat (STB), which is used to transport technicians, parts, and equipment to the turbines. The maintenance activities are optimised over a planning horizon by simultaneously

Two-dimensional cutting and packing problems including irregular items (nesting problems) are common, e.g., in the clothing, paper, glass and leather industries. In the irregular strip packing problem considered in this work a finite number of rotations of convex as well as non-convex polygons with and without holes are permitted. To deal with the geometry of irregular items, direct trigonometry is

The resource allocation problem is among the classical problems in operations research, and has been studied extensively for decades. However, current solution approaches are not able to efficiently handle problems with expensive function evaluations, which can occur in a variety of applications. We study the integer resource allocation problem with expensive function evaluations, for both convex and

Inspired by the retail industry, we consider a stochastic inventory routing problem where retailers are replenished from a central warehouse using a time-based shipment consolidation policy. Such a time-based dispatching policy, where retailers facing stochastic demand are repetitively replenished at fixed times, is essential in practice. It allows for easy incorporation with dependent up- and downstream

Increases in last-mile transport contribute to congestion and pollution in urban environments. To make deliveries more sustainable, they may be integrated with existing public transport infrastructure, e.g., metros or trams. This integration can rely on alternative operational modes: shared infrastructure lets passenger and cargo vehicles share the same rail network, whereas shared vehicles simultaneously

In this paper, we propose a novel operational law for calculating the credibility distribution of monotone functions of independent regular fuzzy numbers to study the project scheduling problem with partially (or fully) fuzzy activity durations. In this regard, we formulate three corresponding types of fuzzy models, namely the α-cost minimization, the credibility maximization and the time-cost trade-off

Bitcoin derivatives positions are maintained with a self-selected margin, which is often too low to avoid automatic liquidation by the exchange, without notice, especially during periods of excessive volatility. Indeed, according to CryptoQuant, almost $80 billion of positions on centralised exchanges were liquidated during 2021, that is an average of over $200 million per day. So hedgers of bitcoin

We consider a routing problem where orders are transported just-in-time from several suppliers to an original equipment manufacturer (OEM). This implies that shipments cannot be picked up before their release date when they are ready at the supplier and should be delivered as close as possible to their due date to the OEM. Every shipment may have a distinct due date but all shipments loaded onto the

This work considers an omnichannel retailer selling a product with market demand uncertainties to customers in different regions through an e-store and multiple brick-and-mortar stores. The retailer also manages online product returns by selecting appropriate return policies. A robust omnichannel pricing and ordering optimization model is proposed with two, i.e., a full-refund and a no-refund, return

Original brand consumables and remanufactured consumables are provided in the after-sales market, and in recent years the entry of compatible consumables provides a new option for consumers. Compared with original brand consumables, remanufactured and compatible consumables enjoy a cost advantage, but they suffer from different consumer trust discounts in the market. In order to capture the scenarios

Dealing with multi-objective problems by using generation methods has some interesting advantages since it provides the decision-maker with the complete information about the set of non-dominated criterion vectors (Pareto front) and a clear overview of the different trade-offs of the problem. However, providing many solutions to the decision-maker may also be overwhelming. As an alternative approach

Weighted voting games are simple games that can be represented by a collection of integer weights for each player so that a coalition wins if the sum of the player weights matches or exceeds a given quota. It is known that a simple game can be expressed as the intersection or the union of weighted voting games. The dimension (codimension) of a simple game is the minimum number of weighted voting games

This study focuses on public or private organisations with a large set of operation units. Central managers in these organisations face asymmetric information on the operating costs of sub-units and wish to incentivise them to reveal their minimal costs. In this paper, best practice regulation is implemented to deal with the asymmetric information via a regulation game. In the regulation game, the

Modern wholesale electricity markets often have producers who exercise market power. The standard way to model market power in an oligopoly with a competitive fringe is by using Mixed Complementarity Problems (MCPs) and conjectural variations. However, such models can lead to myopic (sub-optimal) behaviour for oligopolists. We first build on existing literature to show that an oligopoly with a competitive

Abstract not available

Abstract not available

To analyze a strategic conflict involving composite decision makers (CDMs), this paper uses the methodology of the Graph Model for Conflict Resolution (GMCR). A CDM is a group of individuals with differing decision characteristics conservative or aggressive any one of whom can make a decision on behalf of the group. In our model, a conservative CDM makes moves that take into account the interests of

The enormous amount of containers handled at ports hampers the efficiency of terminal operations. The optimization of crane movements is crucial for speeding up the loading and unloading of vessels. To this end, the premarshalling problem aims to reorder a set of containers placed in adjacent stacks with a minimum number of crane movements, so that a container with an earlier retrieval time is not

We develop a framework for forecasting multivariate data that follow known linear constraints. This is particularly common in forecasting where some variables are aggregates of others, commonly referred to as hierarchical time series, but also arises in other prediction settings. For point forecasting, an increasingly popular technique is reconciliation, whereby forecasts are made for all series (so-called

In this study, we develop a novel method to simulate multidimensional diffusions with sticky boundaries for which the Euler scheme fails. We approximate the sticky diffusion process by a multidimensional continuous-time Markov chain (CTMC) that can be easily simulated. We provide two approaches to construct the CTMC. In the first approach, we approximate the infinitesimal generator of the sticky diffusion

The problem of integrated production and transportation scheduling, commonly faced by make-to-order manufacturers under a commit-to-delivery business mode, is known to be strongly NP-hard. In this study, we propose two new exact algorithms to solve the problem with order acceptance decisions also taken into account. These algorithms can achieve polynomial or pseudo-polynomial running times in several

Cybersecurity risk modeling and pricing are becoming a spotlight in actuarial science and operational research. This paper pertains to the analysis of the cybersecurity risks involved in the fog computing technology which has been intensively deployed in assorted Internet of Things (IoT) applications. To this end, a class of structural models are established to study the inherent cyber risk propagation

The ranking aggregation problem is gaining attention in different application fields due to its connection with decision making. One of the most famous ranking aggregation methods can be traced back to Kemeny in 1959. Unfortunately, the problem of determining the result of the aggregation proposed by Kemeny, known as Kemeny ranking as it minimizes the number of pairwise discrepancies from a set of

Availability of working capital is a challenge for the smooth functioning of any supply chain, particularly when the manufacturer is financially distressed. This gives rise to the issue of selection of optimal supply chain finance programmes. Addressing the limited working capital issue of a financially distressed manufacturer, we construct in this study a Stackelberg game model of a dual-channel supply

We consider optimizing a truck's choice of path and speed profile to minimise fuel consumption, exploiting real-time predictive information on dynamically varying traffic conditions. Time-varying traffic conditions provide particular challenges, both from network-level interactions (e.g. slowing to consume more fuel locally may be beneficial to avoid congested periods downstream) and link-level phenomena

This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial interbank network. We prove that this problem is, generically, NP-hard. We focus on objective functions generated by systemic risk measures under shocks to the financial network.

In this paper, we use the term “co-opetition” to describe situations where competitors collaborate on value-creating activities to reduce their R&D costs, improve expensive development processes, increase the effectiveness and efficiency of their green product development, and increase supply chain sustainability. We use a game-theoretic approach to see how co-opetition affects the price and environmental

Investigating stability of stochastic programs with respect to changes in the underlying probability distributions represents an important step before deploying any model to production. Often, the uncertainty in stochastic programs is not perfectly known, thus it is approximated. The stochastic distribution’s misspecification and approximation errors can affect model solution, consequently leading

Motivated by the asymmetric information inherent to cyberwarfare, we examine a game of deterrence between an attacker and a defender in which the defender can signal its retaliatory capability but can only imperfectly attribute an attack. We show that there are equilibria in which the defender sends noisy signals to increase its expected payoff. In some equilibria, the defender can use signaling to

Parcel logistics services play a vital and growing role in economies worldwide, with customers demanding faster delivery of nearly everything to their homes. To move larger volumes more cost effectively, express carriers use sort technologies to consolidate parcels that share similar geographic and service characteristics for reduced per-unit handling and transportation costs. This paper focuses on

We study situations where agents can form or sever links in a network: what agents can do exactly is described by effectivity functions. A power index assigns to such an effectivity function a number for each agent, measuring the opportunities of that agent. We characterize a class of power indices by four axioms: the Transfer Property, the Dummy Property, Symmetry, and Network Neutrality. As a corollary

Initial Coin Offering (ICO) is a new form of financing instrument for start-up firms. The firm issues tokens (or coins) in the ICO phase to raise capital to build capacity for its project. If the project is successful, the firm will provide product in subsequent periods and this product can only be accessed via tokens which can be traded over an exchange market. In this paper, we propose a model to

The networked structure of investor relationship has been documented by many researches. This paper proposes a dynamic model based on investor network, and investigate the impacts of investor interactions on market stability. Two learning patterns are taken into account. The herd behavior is characterized with the imitation and diffusion of trading strategies in investor network. The behavioral equilibria

Modern life insurance policies embed a surrender option that entitles policyholders to terminate their policy early for its cash value. Mass surrenders-spiking surrenders of life insurance policies within a short period-are widely documented prior to many life insurer failures, but their impacts on insurers are rarely quantified. This paper builds a model of mass surrenders in a heterogeneous pool

Given the emergence of two-echelon distribution systems in several practical contexts, this paper tackles, at the strategic level, a distribution network design problem under uncertainty. This problem is defined as the two-echelon stochastic multi-period capacitated location-routing problem (2E-SM-CLRP). It considers a network partitioned into two capacitated distribution echelons: each echelon involves

This study extends the multi-depot vehicle scheduling problem with time windows (MDVSPTW) to the case of electric vehicles which can recharge at charging stations located at any point of the service operation area. We propose a mixed-integer nonlinear model for the electric bus multi-depot vehicle scheduling problem with time windows (EB-MDVSPTW). Our formulation considers not only the operational

In this special issue, 23 research papers are published focusing on COVID-19 and operational research solution techniques. First, we detail the process from advertising the call for papers to the point where the best papers are accepted. Then, we provide a summary of each paper focusing on applications, solution techniques and insights for practitioners and policy makers. To provide a holistic view

In this paper, we address the Continuous Multifacility Monotone Ordered Median Problem. The goal of this problem is to locate p facilities in Rd minimizing a monotone ordered weighted median function of the distances between given demand points and its closest facility. We propose a new branch-and-price procedure for this problem, and three families of matheuristics based on: solving heuristically

Real-life parallel machine scheduling problems can be characterized by: (i) limited information about the exact task duration at the scheduling time, and (ii) an opportunity to reschedule the remaining tasks each time a task processing is completed and a machine becomes idle. Robust optimization is the natural methodology to cope with the first characteristic of duration uncertainty, yet the existing

Dynamic vehicle routing problems (DVRPs) arise in several applications such as technician routing, meal delivery, and parcel shipping. We consider the DVRP with stochastic customer requests (DVRPSR), in which vehicles must be routed dynamically with the goal of maximizing the number of served requests. We model the DVRPSR as a multi-stage optimization problem, where the first-stage decision defines

The refueling station location problem with routing (RSLP-R) is defined as a maximal coverage problem that locates alternative fuel refueling stations (AFSs) on a road network to maximize the refueled alternative fuel vehicle flows by considering the limited range of vehicles and the willingness of drivers to deviate from their paths for refueling. In this study, we introduce the robust counterpart

We study the prize-collecting job sequencing problem with one common and multiple secondary resources. In this problem, a set of jobs is given, each with a profit, multiple time windows for its execution, and a duration during which it requires the main resource. Each job also requires a preassigned secondary resource before, during, and after its use of the main resource. The goal is to select and

Inspired by real-world applications such as the assignment of pupils to schools or the allocation of social housing, the one-sided matching problem studies how a set of agents can be assigned to a set of objects when the agents have preferences over the objects, but not vice versa. For fairness reasons, most mechanisms use randomness, and therefore result in a probabilistic assignment. We study the

Although most takeover theories presume the acquirers initiate the transactions, many transactions are in reality initiated by targets. This paper attempts to understand such a target’s sellout timing and pricing decisions by developing a target-initiated model, in which the firm randomly and periodically meets high- and low-type acquirers and makes take-it-or-leave-it price offers. The model captures

In this paper, we consider the estimation of semiparametric spatial stochastic frontier (SF) models, in which the spatial dependence is modeled by adding the spatially lagged dependent variable as an additional independent variable (following the convention of spatial autoregressive models) and specifying various spatial structures on the inefficiency and/or idiosyncratic error. Thus, the proposed

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on “standard” formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also reviewed and briefly discussed. Subsequently, we report

We investigate how to secure reliable access to personal protective equipment (PPE) in pandemics, which are characterized by random occurrences and durations, at the lowest expected cost. The policymaker’s strategy is based on a mix of (1) holding ready-to-use strategic stockpile that is acquired at regular price but incurs a holding cost, (2) building partnership with PPE manufacturers to relocate

Cleaning debris in urban areas after major disasters is very relevant to inhabitants to recover from their effects. In natural disasters, an unexpected and large area can be affected. Moreover, the time and the costs to perform the cleaning operations can be very high. In this work, the integrated multi-period scheduling routing problem to clean debris (SRP-CD) after major disasters is investigated