The global sports industry is extremely competitive. We focus on ice hockey and propose a (largely) costless reform to its operations that can potentially enhance the sport’s popularity by increasing the number of goals. The reform optimizes a logistic convention on the use of on-ice sides and off-ice benches, which affects the amount of attacking play and within-game scoring dynamics through the players’

In this note we introduce multivariate extensions to the bivariate discrete analogue to continuous probability distributions proposed in Barbiero [Annals of Operations Research, doi: 10.1007/s10479-019-03388-8, 2019]. We furthermore show that identical properties of the bivariate case also hold for n-variate discrete analogues.

In this paper a new Data Envelopment Analysis (DEA) target setting approach is proposed based on a modification of the discrete Raiffa solution of bargaining problems. It is a multistage method that in the first step moves along the segment towards the ideal point, advancing along it as much as possible. If that first intermediate operating point is weak efficient (i.e. some input or output dimensions

In this paper, we consider due-window assignment scheduling in the proportionate flow shop setting with position-dependent weights where the weights depend on the position in which a job is scheduled. Under the common due-window (CONW) and slack due-window (SLKW) assignment methods, the location of the window and its properties are established. The objective is to determine the sequence of all jobs

Fairness has several interpretations in sports, one of them being that the rules should guarantee incentive compatibility, namely, a team cannot be worse off due to better results in any feasible scenario. The current seeding regime of the most prestigious annual European club football tournament, the UEFA (Union of European Football Associations) Champions League, is shown to violate this requirement

We address the problem of modifying vertex weights of a block graph at minimum total cost so that a predetermined set of p connected vertices becomes a connected p-median on the perturbed block graph. This problem is the so-called inverse connected p-median problem on block graphs. We consider the problem on a block graph with uniform edge lengths under various cost functions, say rectilinear norm

In this paper, we study the project staffing problem with discrete time/resource trade-offs to minimise the personnel staffing budget. This staffing problem embeds activity scheduling flexibility by incorporating the project scheduling problem into the personnel staffing problem to improve the quality of the staffing plan. In addition, we introduce extra demand scheduling flexibility resulting from

In this paper a stochastic districting problem is investigated. Demand is assumed to be represented by a random vector with a given joint probability distribution function. A two-stage mixed-integer stochastic programming model is proposed. The first stage comprises the decision about the initial territory design: the districts are defined and all the territory units assigned to one and exactly one

An important yet largely unexamined issue is how the interaction between deforestation and pollution affects economic and environmental sustainability. This article seeks to bridge the gap by introducing a dynamic model of pollution accumulation where polluting emissions can be mitigated and the absorption efficiency of pollution sinks can be restored. We assume that emissions are due to a production

We propose an efficient extension of the Myerson value for games with communication graph structure. Define a quotient game on set of the components of the graph, in which each component acts as a component-player. Then, each player in a component receives his payoff according to the Myerson value and an equal share of the surplus of the Shapley value obtained by the component in the quotient game

This study develops an inventory model to solve the problems of supply uncertainty in response to demand which follows a Poisson distribution. A positive aspect of this model is the consideration of random inventory, delivery capacities and supplier's reliability. Additionally, we assume supplier capacity follows an exponential distribution. This inventory model addresses the problem of a manufacturer

A logical strategy to contain the Covid-19 pandemic is to completely isolate everyone for 2 weeks (the incubation period of the virus). However, such a strategy can have prohibitive economic and social costs and, therefore, will be difficult to implement. At the same time, the current situation is leading to an expanding humanitarian, health and economic crisis. Based on principles of the Theory of

Robust portfolio optimization refers to finding an asset allocation strategy whose behavior under the worst possible realizations of the uncertain inputs, e.g., returns and covariances, is optimized. The robust approach is in contrast to the classical approach, where one estimates the inputs to a portfolio allocation problem and then treats them as certain and accurate. In this paper we provide a categorized

Counterinsurgencies are a type of violent struggle between state and non-state actors in which one group attempts to gain or maintain influence over a certain portion of the population. When an insurgency (i.e., non-state actor) challenges a host nation (i.e., state actor), often an external counterinsurgent force intervenes. While researchers have categorized insurgencies with social science techniques

We develop a multi-period stochastic optimization framework for identifying operating reserve requirements in power systems with significant penetration of renewable energy resources. Our model captures different types of operating reserves, uncertainty in renewable energy generation and demand, and differences in generator operation time scales. Along with planning for reserve capacity, our model

Portfolios constructed by the classical mean-variance model are very sensitive to outliers. We propose the use of a non-parametric estimation method based on statistical data depth functions. Specifically, we exploit the notion of the weighted \(L^{p}\) depth function to obtain robust estimates of the mean and covariance matrix of the asset returns. This approach has the advantage to be independent

Planning and scheduling of operating rooms (ORs) is important for hospitals to improve efficiency and achieve high quality of service. Due to significant uncertainty in surgery durations, scheduling of ORs can be very challenging. In this paper, surgical case scheduling problem with uncertain duration of surgeries in multi resource environment is investigated. We present a two-stage stochastic mixed-integer

In the classical Travelling Salesman Problem (TSP), the objective function sums the costs for travelling from one city to the next city along the tour. In the q-stripe TSP with [Formula: see text], the objective function sums the costs for travelling from one city to each of the next q cities in the tour. The resulting q-stripe TSP generalizes the TSP and forms a special case of the quadratic assignment

High school timetabling (HSTT) is a well known and wide spread problem. The problem consists of coordinating resources (e.g. teachers, rooms), times, and events (e.g. lectures) with respect to various constraints. Unfortunately, HSTT is hard to solve and just finding a feasible solution for simple variants of HSTT has been proven to be NP-complete. We propose a new modeling approach for HSTT using

This paper sets out the development of a methodological framework for detailed evaluation of public health strategies for alcohol harm reduction to meet UK policy-makers needs. Alcohol is known to cause substantial harms, and controlling its affordability and availability are effective policy options. Analysis and synthesis of a variety of public and commercial data sources is needed to evaluate impact

This paper tackles linear programming problems with data uncertainty and applies it to an important inventory control problem. Each element of the constraint matrix is subject to uncertainty and is modeled as a random variable with a bounded support. The classical robust optimization approach to this problem yields a solution with guaranteed feasibility. As this approach tends to be too conservative

In network interdiction problems, evaders (e.g., hostile agents or data packets) are moving through a network toward targets and we wish to choose locations for sensors in order to intercept the evaders. The evaders might follow deterministic routes or Markov chains, or they may be reactive, i.e., able to change their routes in order to avoid the sensors. The challenge in such problems is to choose

In this paper, we consider the batch mode reinforcement learning setting, where the central problem is to learn from a sample of trajectories a policy that satisfies or optimizes a performance criterion. We focus on the continuous state space case for which usual resolution schemes rely on function approximators either to represent the underlying control problem or to represent its value function.

Network Growth Models such as Preferential Attachment and Duplication/Divergence are popular generative models with which to study complex networks in biology, sociology, and computer science. However, analyzing them within the framework of model selection and statistical inference is often complicated and computationally difficult, particularly when comparing models that are not directly related or

We tackle home healthcare planning scenarios in the UK using decomposition methods that incorporate mixed integer programming solvers and heuristics. Home healthcare planning is a difficult problem that integrates aspects from scheduling and routing. Solving real-world size instances of these problems still presents a significant challenge to modern exact optimization solvers. Nevertheless, we propose

Employee scheduling is a well known problem that appears in a wide range of different areas including health care, air lines, transportation services, and basically any organization that has to deal with workforces. In this paper we model a collection of challenging staff scheduling instances as a weighted partial Boolean maximum satisfiability (maxSAT) problem. Using our formulation we conduct a comparison

This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form

In the variant of the well studied nurse rostering problem proposed in the Second International Nurse Rostering Competition, multiple stages have to be solved sequentially which are dependent on each other. We propose an integer programming model for this problem and show that a set of newly developed extensions in the form of additional constraints to deal with the incomplete information can significantly

Condition-based monitoring is used as part of predictive maintenance to collect real-time information on the healthy status of a vessel engine, which allows for a more accurate estimation of the remaining life of an engine or its parts, as well as providing a warning for a potential failure of an engine part. An engine failure results in delays and down-times in the voyage of a vessel, which translates

Conventional wisdom suggests that competition from a third-party remanufacturer lowers the original equipment manufacturer (OEM)’s profits. In this paper, we show that this may not hold for the remanufacturing competition when the presence of remanufactured products affects the consumers’ perceived value of new products. We introduce two new effects of remanufacturing: (1) third-party remanufacturer

Determining the best location to serve companies’ profitability and sustainability is becoming more crucial every day, since the rivalry between companies is getting more intense. The transformation of economies from manufacturing orientation towards service based activities has resulted in a growing contribution of the service based economy in gross domestic product and workforce of developing countries

The 0/1 knapsack polytope is the convex hull of all 0/1 vectors that satisfy a given single linear inequality with non-negative coefficients. This paper provides a comprehensive overview of knapsack polytopes. We discuss basic polyhedral properties, (lifted) cover and other valid inequalities, cases for which complete linear descriptions are known, geometric properties for small dimensions, and connections

Cooperative (co-op) advertising is an arrangement between manufacturer and retailer, where two members initiate their respective advertising to help develop brand, motivate sales, and other purposes. This paper focuses on cooperative advertising in a supply chain consisting of one manufacturer and one retailer. As two basic elements of a supply chain, the channel power structure and information structure

Motivated by a real-life application, this research considers the multi-objective vehicle routing and loading problem with time window constraints which is a variant of the Capacitated Vehicle Routing Problem with Time Windows with one/two-dimensional loading constraints. The problem consists of routing a number of vehicles to serve a set of customers and determining the best way of loading the goods

This study analytically examines online promotions with gift rewards based on data from a Chinese tea retailer, Huiliu. Gift rewards benefit Huiliu by improving promotional performance. However, they generate operational problems, especially by increasing the costs of holding gift inventory. To address Huiliu’s concerns about gift rewards, we first conduct an empirical study based on Huiliu’s promotional

This study investigates the inventory sharing policy of a professional optics product supply chain based on a real case study. The supply chain sells a product via two sales agents with equal power. The manufacturer receives a single order from each agent at the beginning of the selling season. Stock is kept in the manufacturer’s central warehouse. Thus, the agents hold virtual inventory only. To obtain

In the last century, many infectious diseases have been completely eradicated or significantly reduced because of childhood vaccinations. Ample evidence suggests that low vaccination coverage in developing countries is caused by vaccine stockout and high rates of vaccine wastage. Wastage occurs when a vaccine vial is physically damaged or exposed to extreme temperatures, or when doses from an open

The validity of performance evaluation is determined by, and therefore greatly influenced by, the accuracy of data set. To address such imprecise and negative data problems widely spread in the real world, this paper proposes a second-order cone based robust data envelopment analysis (SOCPR-DEA) model, which is more robust to data variety. Further, this new computational tractable model is applied

Demand forecasting for the fashionable products is still a difficult task for both academia and industry regardless of how many effective approaches have been investigated and studied in the literature. The arriving of big data era leads to a round of revolution on the demand forecasting for the fashionable products, and at the same time, it makes a great challenge to traditional forecasting methods

We consider a bilateral supply chain with a downstream manufacturer and an upstream farmer. The manufacturer makes two sourcing decisions: Whether to join the fair trade movement and whether to use organic or conventional (non-organic) cotton in her product. The manufacturer’s sourcing strategy affects the determination of the wholesale price, the farmer’s production cost, and consumers’ purchasing

The integrated care service districting (ICSD) problem is an important logistics decision that the elderly care structures (ECS) face when designing service networks to deliver integrated care to the elderly. The ICSD problem, which aims to prepare enhanced care worker recruitment and training plans for all well-designed service districts, is formulated as a multi-objectives mixed integer nonlinear

Commonly encountered in cold chain logistics, third-party distribution firms are required to deliver temperature-sensitive food products to various retailers with two kinds of time-window constraints: (1) the delivery service must begin within the time windows imposed by the retailers (called node time windows) and (2) each vehicle route is available only in a predefined time interval prescribed by

We study the delivery of mobile medical services and in particular, the optimization of the joint stop location selection and routing of the mobile vehicles over a repetitive schedule consisting of multiple days. Considering the problem from the perspective of a mobile service provider company, we aim to provide the most revenue to the company by bringing the services closer to potential customers

In business practice the misalignment between frequent inventory adjustments and a sticky price is common. Motivated by Pipi Milk, a diary manufacturer who commits its customer at a fixed price for a whole year meanwhile weekly replenishes its cheese product stock at a specific batch size, this paper develops an integrated constant pricing and inventory control model in a periodic-review system with

In disaster relief, one major concern is to have an efficient network to supply and distribute critical items such as blood to the affected areas. Based on a real case study, a tailored disaster relief blood supply chain problem is carried out for the responsive and reliable supply of blood. The case study necessitates incorporating three criteria, (1) urgency (U) of the injured and their priority-based

We investigate the impact of power structures on the production and pricing strategies in a decentralized subcontracting assembly system consisting of two suppliers (key supplier and subcontractor) and one manufacturer (assembler). The key supplier, who is also the general contractor, negotiates with the manufacturer and assigns partial component production to the subcontractor. We first identify a

It is seen that the trade credit period has an important role in real business world. In this article, an inventory model has been developed by considering stochastic lead time demand with lead time crashing cost. Here, also to get the impact between credit period and lead time, a lead time dependent credit period has been considered. In this model, considering partial back-order, the effect of lost

This paper studies a location-inventory problem in a closed-loop supply chain by considering the demand and sales in the primary and secondary markets. Based on a real business program in a big e-commerce company, we develop a mixed-integer nonlinear programming model with a single hybrid production-recovery center, multiple hybrid distribution-collection centers, and many customer zones. As a closed-loop

Many retailers nowadays operate in an Internet-enabled dual-channel supply chain setting, referred to as “click and mortar”. In such a structure, products and services are delivered through both online B2C (business-to-consumer e-tail) and offline B2C (traditional brick and mortar retail) channels. In this paper, we develop and present a unified modeling approach that reflects a real-world dual-channel

In this paper, we examine the impact of manufacturers’ dishonest reports of product sustainability. We first investigate the Volkswagen emissions scandal and Wal-Mart fake organic food scandal in terms of the overstatement of product sustainability. Based on these two cases, we construct a two-echelon supply chain model consisting of one manufacturer and one retailer. The supply chain members can use

The concept “new retail” in e-commerce is to establish an offline channel and integrate it with the online retail channel. The development of new retail encounters three main problems: locations of the offline stores, the price competition with the traditional online retail, and the difficulty in consumer recognition in the two channels. In this paper, we present a duopoly model consisting of a new

Nowadays, the demand of small-series production and quick response become more and more important in textile supply chains. To meet the increasing trend of customization in garment production, forecast based supply chain model is not suitable any more. Demand-driven garment supply chain is developed and employed more and more. However, there are still many defects in current model for demand-driven

Performance impacts of ordering and production control policies in the presence of capacity disruptions are studied on the real-life example of a retail supply chain with product perishability considerations. Constraints on product perishability typically result in reductions in safety stock and increases in transportation frequency. Consideration of the production capacity disruption risks may lead