Abstract Traditional behavior-based pricing (BBP) literature suggests that firms should offer lower prices to incentivize new customers to switch. However, at the time of switch, customers are often uncertain about their true needs or valuations of the product. Accordingly, they may experience repeat-purchase or switch-purchase regret, depending on whether they have bought a product from the same brand

Abstract In this paper, we consider the problem of allocation of Emergency Vehicles (EVs) to Rescue Centers (RCs). The objective is to improve the operational response of the Fire and Rescue Services (SDIS) in France. More precisely, we focus on the mid-term management, and on the process of redeployment of EVs in RCs according to the evolution of requirements. At this level of decision, we do not

Abstract Due to constraints on pack sizes in which products are shipped to retail stores, excess inventory can accumulate in stores. In order to optimize the allocation of store space between storage and customer-facing areas, simple expressions are required for backroom inventory levels that can be inserted into optimization models. This paper systematically investigates the effect of pack size constraints

Abstract We solve a periodic supply vessel planning problem under demand and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule under uncertain demand at the installations and uncertain weather

Abstract The paper analyzes a multi-item inventory system, using independent (R,Q) policies. The aim is to minimize the average stock level while keeping a weighted (across items) fill rate service level at a given target. The paper explores whether the optimal order sizes and the optimal safety factors are aligned with the ABC classification. Our results show that A items should be ordered more frequently

Abstract This paper concerns with the total weighted tardiness on a single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, four heuristic methods are developed to solve real size applications including the size of

Abstract Various optimization tools have been used in industry to facilitate production planning at different levels of aggregation. Choosing the interoperability mechanisms of these systems, such as the planning frequencies, the information passed between them and the interpretation that other systems must make of them, has always been a challenge. This work focusses on production planning at the

Abstract With the rapid development of economy, China faces a considerable challenge from environmental problems especially with the waste of gas pollution emitted by China’s industry. To assess the environmental performance of China’s industry, this paper proposes a new generalized equilibrium efficiency frontier data envelopment analysis (GEEFDEA) approach that considers waste gases as undesirable

Abstract Hospitals are dealing with the daunting task of scheduling patients in operating rooms under a limited budget, time, and staff. This article finds the optimal schedule of surgeries by minimizing operating rooms’ idle times while maximizing the number of scheduled surgeries during the most effective and desirable time windows. Surgeries during ideal time windows are encouraged by assigning

(2021). Statement of retraction. INFOR: Information Systems and Operational Research. Ahead of Print.

Abstract This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-term strategic uncertainty and short-term operational uncertainty in a single optimization model. The model supports wind farm owners in making strategic decisions regarding the

Retailers are increasingly offering customers a seamless shopping experience through all available shopping channels. However, when should an online retailer open an offline showroom or a physical store to implement an omni-channel strategy? In this study, we establish profit models in four scenarios and obtain the conditions under which an online retailer can be profitable in different channels. The

This paper concerns the total weighted tardiness on single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, 4 (four) heuristic methods are developed to solve real size applications including the size of 1000 jobs. The

In real-world environments, selecting the right contractor is an important issue which considerably influences completion time, total cost and quality of performing the project. This paper deals with the multi-mode resource constrained project scheduling problem (MRCPSP) and contractor selection (CS) in an integrated manner. In fact, each activity is assigned to a contractor, an execution mode is selected

A large portion of expenses in the forest industries is associated with wood supply procurement. Numerous suppliers are involved and securing wood supply contracts with competitive prices is a constant challenge for procurement managers. A major difficulty is the procurement exposure to various sourcing risks including the start of the spring thaw, contract breach, or unreliability of suppliers. A

Abstract Consignment is a form of business arrangement, in which a vendor places goods at a retailer’s location without receiving payment until the products are sold. This paper examines consignment with consumer non-defective returns behaviour, where the upstream vendor makes a contract with the downstream retailer. The vendor decides what the consignment and refund prices are, and the retailer chooses

Abstract The current paper aims to provide a novel approach for the assignment of students to elective courses using historical records of course capacities and student demand. With this aim, we establish a link between the course assignment problem and the airline seat allocation modeling of Revenue Management. An analogy is set up relying on the assumption that the students form distinct groups and

Abstract Supply chain networks are complex and often proprietary, which implies that on the most part, the structure of a company’s supply chain is not well known nor accessible. This research investigates supply chain network topology, properties and supply network evolution using a data-driven approach. The key idea is to construct a sample set of data from a financial source and examine it in the

Abstract In many real-world situations, there are a fraction of defective items in a received lot whose quality should be evaluated before storage. In this article, we address the joint ordering, pricing, and inspection planning problem for a retailer facing price-sensitive demand and stochastic supply lead-time. The fraction of nonconforming items in a received lot follows a beta distribution and

Abstract In this note, we analyze location problems where the distance (time) to get to the destination by air is affected by winds. We propose two models: the asymmetric Weber location problem and the round-trip Weber location problem. The problems are analyzed and solved.

DEA (Data Envelopment Analysis) is a nonparametric approach that has been used to estimate fuzzy portfolio efficiency. In this paper, we propose an approach under the fuzzy theory framework that can both improve the DEA frontier and suggest a replicable benchmark for investors. We first construct an improved DEA model using the proposed approach and then investigate the relationships among the evaluation

Abstract The dynamic facility layout problem (DFLP) deals with the arrangement of facilities/departments in a factory for different periods so that the location of the facilities can be changed from one period to another one. Traditionally, this problem is formulated to minimize the sum of material handling and rearrangement costs in the planning horizon by assuming that all parameters are deterministic

Abstract Along with the popularity of online shopping, the cash-back industry is witnessing dramatic development. Under this backdrop, retailers who sell products with network externalities make different decisions about affiliating with cash-back sites. In this paper, we set up a cash-back model considering network externalities. Our goal is to identify the condition under which it is profitable for

Abstract This study analyzes how the new online platform-selling format affects the optimal co-operative advertising choices of both the manufacturer and the e-commerce platform (e-tailer), and explores the effects of the e-tailer’s contractual forms and commission fees on these choices. In the model, the manufacturer can decide its advertising expenditure as well as the level of participation in the

Abstract In this article, we study the influences of manufacturer rebate on the outcomes of the channel members in a green supply chain, where the retailer has private information about market demand. We find that, (1) manufacturer rebate is good for the channel members, however, the manufacturer takes a lower share of the incremental profit than the retailer; (2) the value of manufacturer rebate for

Drawing on statistical learning theory, we derive out-of-sample and optimality guarantees about the investment strategy obtained from a regularized portfolio optimization model which attempts to exploit side information about the financial market in order to reach an optimal risk-return tradeoff. This side information might include for instance recent stock returns, volatility indexes, financial news

Abstract To reduce the environmental pollution of Waste Electrical and Electronic Equipment (WEEE), the government has promulgated take-back legislation. For the producer, he should consider collection effort and remanufacturing design response to collection goal and remanufacturing goal. In this article, we develop two models: (1) model only with remanufacturing design and (2) model with both collection

(2020). Preface to the special issue of INFOR on “continuous optimization and applications in machine learning and data analytics”. INFOR: Information Systems and Operational Research: Vol. 58, Special Issue on 'Continuous Optimization and Applications in Machine Learning and Data Analytics', pp. 167-167.

Abstract Sourcing overseas enables customers to experience high-quality products, especially for those in the developing countries/regions. This induces many brand-owners to decide product diversification by selling both imported products (high quality reliability) and local products (low quality reliability), although product self-competition occurs and may result in system profit loss. In this paper

Abstract In this paper, a closed-loop supply chain network design problem is developed. In the proposed model, expected returned products is estimated as a function of return price and if the amount of returned products is less than the expected amount, decision makers have some choices such as more advertising, incentives (extra cost) for returning more products. Different quality levels are considered

Abstract We study a parallel-queue system with Poisson arrivals, in which a dispatcher sends the incoming traffic to K queues using Size Interval Task Assignment (SITA) policy that aims to equalize the performance of all queues. We study existence and uniqueness of the allocation thresholds for a large set of performance functions of the queues. We also provide a family of performance functions of

Abstract In this study, a new mathematical programming approach for solving the joint timetabling and train stop planning problem in a railway line with double-track segments is proposed. This research aims to design an optimized train timetable subject to the station-capacity and time-dependent dwell time constraints. The objective function is to maximize the railway infrastructure capacity by minimizing

Abstract Product innovation and service upgrades are effective measures for firms to improve their competitiveness. Considering the upgrading of the installed customers (IU), the upgrade strategy of a platform firm usually follows two principles, namely, the derived principle (i.e., the basic product still operates when the new derived product is released) or updated principle (i.e., the basic product

Real industrial studies often give rise to complex optimization problems involving mixed variables and time consuming simulators. To deal with these difficulties we propose the use of a Gaussian process regression surrogate with a suitable kernel able to capture simultaneously the output correlations with respect to continuous and categorical/discrete inputs without relaxation of the categorical variables

Abstract Robust optimization (RO) has attracted much attention from the optimization community over the past decade. RO is dedicated to solving optimization problems subject to uncertainty: design constraints must be satisfied for all the values of the uncertain parameters within a given uncertainty set. Uncertainty sets may be modeled as deterministic sets (boxes, polyhedra, ellipsoids), in which

A methodology is presented that determines the staff requirements for a baggage handling operation at an international airport facing high demand. It consists of two sequentially solved integer linear programming models. The first model determines the handler requirement using historical demand data and incorporates the operation’s spatial constraints. The second model, taking as input the results

In service industries such as restaurants and tourism, empirical findings show that uninformed customers may consider queues as a signal of service quality and choose to join a longer queue. Service managers become aware of this phenomenon and stimulate customer purchase by maintaining a queue. In this paper, we explore issues related to the balance between herding and congestion for service systems

This article addresses the daily scheduling of surgeries in an operating theatre. The problem consists of a set of surgical operations that have to be scheduled in identical operating rooms. The operations have uncertain durations, require setup activities before and after the surgical act and are assigned to surgeons who have to perform the surgical part. The objective is to find the best sequence

Analysing conflicts in large optimization problems is an intricate and difficult task. In this paper we present a tool for infeasible LP, to guide the decision maker towards an adequate strategy for dealing with the infeasibility. We propose a mathematical formulation for the ranking of the optimal values and solutions among all feasible subsets of constraints, that is, to find (feasible) clusters

Recently, Peña and Soheili presented a deterministic rescaling perceptron algorithm and proved that it solves a feasible perceptron problem in O(m2n2 log (ρ−1)) perceptron update steps, where ρ is the radius of the largest inscribed ball. The original non-deterministic rescaling perceptron algorithm of Dunagan and Vempala is based on systematic increase of ρ, while the proof of Peña and Soheili is

(2019). CORS 60th anniversary special issue: celebrating recent Canadian contributions to operational research. INFOR: Information Systems and Operational Research: Vol. 57, CORS 60th Anniversary Special Issue, pp. 495-495.

The Ontario Ministry of Natural Resources and Forestry uses amphibious airtankers to help control forest fires in the province of Ontario. Their airtankers are based at airports from which they are dispatched to fires to assist FireRanger crews that work on the ground. Airtanker systems can be modelled as spatial queueing systems with fires as customers that arrive at rates that vary over both time

Different from previous researches, our study considers a perishable item with collaborative vendor–buyer ordering policy and finite replenishment rate. Furthermore, due to the importance of inventory and capital investment in today’s fuzzy marketing environments, researches in fuzzy collaborative inventory models have become very popular research in recent decades. Therefore, in our integrated model

(2020). Correction. INFOR: Information Systems and Operational Research: Vol. 58, Special Issue on 'Continuous Optimization and Applications in Machine Learning and Data Analytics', pp. 424-424.

Abstract Data envelopment analysis (DEA) models are applied in commercial firms to evaluate their technical, cost and revenue efficiencies. The new models introduced here are based on inverse DEA for preserving cost/revenue efficiency. The commercial institution management seeks to minimize the input costs for a given level of outputs or maximize the revenue of outputs for a specified level of inputs

Adaptive cubic regularization (ARC) and trust-region (TR) methods use modified linear systems to compute their steps. The modified systems consist in adding some multiple of the identity matrix (or a well-chosen positive definite matrix) to the Hessian to obtain a sufficiently positive definite linear system, the so called shifted system. This type of system was first proposed by Levenberg and Marquardt

Abstract The Accumulating Priority Queue model, in which customers accumulate priority as a linear function of their time in the queue, was first introduced by Kleinrock in 1964 under another name. All publications addressing the APQ since then have assumed that customers start accumulating priority credits upon arrival. The model we present herein, called the Delayed Accumulating Priority Queue, entails

(2019). Correction. INFOR: Information Systems and Operational Research. Ahead of Print.

(2019). Editorial. INFOR: Information Systems and Operational Research: Vol. 57, Multidimensional Perspectives in Finance and Investment, pp. 343-344.

Multiple sequence alignment (MSA) represents a basic task for many bioinformatics applications. MSA allows finding common conserved regions among various sequences of proteins or DNA. However, to find the optimal multiple sequence alignment, it is necessary to design an efficient exploration approach that could explore a huge number of possible multiple sequence alignments. As well as, it is required

We analyze symmetric subgame perfect equilibria of the dollar auction in its original format, without the modifications that the literature adopts to rule out overbidding in the game. The game has a continuum of subgame perfect equilibria, generating expected revenues that range from zero to the full value of the contested prize. Such multiplicity of equilibria suggests that the overbidding pattern

This article presents a two-stage workforce scheduling approach for security guards at motor traffic gates. In the first stage, staffing requirements are determined based on analyzing workload variations for each gate. In the second stage, an integer programming model is formulated to assign guards to different work shifts in order to satisfy the staffing requirements of each gate. The objective is

This article studies least-squares approximate policy iteration (API) methods with parametrized value-function approximation. We study several variations of the policy evaluation phase, namely, Bellman error minimization, Bellman error minimization with instrumental variables, projected Bellman error minimization, and projected Bellman error minimization with instrumental variables. For a general discrete-time

In the literature, it has been shown that autocorrelation in service times has a dramatic impact on performance measures in delay systems. Although some studies deal with systems having autocorrelated service times, a general renewal approximation methodology that can incorporate this information in analytical models has not been previously proposed. In this paper, we develop a discrete event simulation

Effective communication between nurses and physician teams on the internal medicine unit is crucial for high quality, safe, and efficient patient care. In our hospital of interest, a large academic health sciences centre, the physical layout of the unit, current admission process, and the presence of three separate physician teams contribute to uneven workload and communication barriers. We address

Data envelopment analysis (DEA) is a nonparametric data-based approach that is used to evaluate the performance of a set of homogeneous units; hence, inputs and outputs play a crucial role in this evaluation. In many technologies, the inputs and outputs are so volatile and complex that even other stochastic events can have an influence in the measurement accuracy. A suitable estimation method can be

This paper is concerned with how to stably arrange the total input resources and output productions when the total outputs can be forecasted in a centralized decision-making environment based on data envelopment analysis (DEA). It usually involves the participation of all individual decision-making units, each contributing in part to the total production. Two stability indexes are defined to assess

We introduce an algorithm for the optimization of problems whose objective functions are evaluated by computationally expensive black-box simulations and for which an analytic description of the objective and its derivatives are not available. We consider the case where two levels of simulation model fidelity are available, namely a high fidelity model that is computationally very expensive to evaluate

The maximum feasible subset problem (maxFS) is this: given an infeasible set of constraints, find a largest cardinality subset that admits a feasible solution. This problem is NP-hard but has been studied extensively for the case of linear constraints, and good heuristic solution algorithms are available. There is a surprisingly large range of applications for algorithms that solve the linear maxFS

We propose to take advantage of symmetry that exists in some quadratic assignment instances when employing genetic or hybrid genetic algorithms to solve such instances. Such symmetry usually exists when the potential sites for the facilities are arranged in a rectangle. We designed a simple and effective approach to identify equivalent solutions if such symmetry exists. We propose three variants of