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

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 the

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 intend

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 context

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 the buyer

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

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. In

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 retailers

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 e-tailer’s

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

The advent of new technologies in the area of transportation has led to the creation of new business models that benefit from their capabilities. Among them, Teo Taxi, a Taxelco project, uses a unique business model: taxi drivers are employees instead of being self-employed. In addition, the company uses only electric vehicles. This shift entails new challenges regarding fleet management and process

This paper discusses the petrol-station replenishment problem with adjustable demands (PSRP-AD). This problem originates from a practical application of fuel delivery, where the main objective is to satisfy all petrol-station demands at a minimal cost. However, the problem includes tanks with adjustable loads while respecting the agreement made between the company and the customers. This agreement

This study develops a mathematical model for an integrated vendor-buyer inventory with defective items and inspection error. We assume an imperfect production process with a known of defective probability. The buyer conducts a 100% quality check. However, due to an imperfect inspection process, the quality-controller may reject a good item as a defective item (Type I error), or accept a defective item

We propose and analyze two mathematical programming models for a production, inventory, distribution and routing problem considering real and relevant features from the furniture industry, such as production sequence-dependent setup times, heterogeneous fleet of vehicles, routes extending over one or more periods of the production planning horizon, multiple time windows and customers’ deadlines, among

The concept of the optimal partition was originally introduced for linear optimization and linear complementarity problems and subsequently extended to semidefinite optimization. For linear optimization and sufficient linear complementarity problems, from a central solution sufficiently close to the optimal set, the optimal partition and a maximally complementary optimal solution can be identified

Most research regarding revenue management in manufacturing has considered only a short-term planning horizon, assuming supply and production data exogenously given. Motivated by the case of the Canadian softwood lumber industry, this paper offers additionally a medium-term visibility for firms with limited capacity and faced with seasonal markets. We propose a demand management process for Make-To-Stock

This paper describes the development of a scheduling tool to help a Canadian shipping company optimize the routing and scheduling of their ships and allocate the right assets to the right cargo. The problem can be formulated as a variant of the vehicle routing problem with pickup and delivery, and it is solved by adapting a tabu search heuristic originally developed for the latter problem. The decision

We introduce the generalized constrained maximum-entropy sampling problem (GCMESP) as a common generalization of the ordinary constrained maximum-entropy sampling problem (CMESP) and the constrained D-optimality problem (CDOPTP). Exact algorithms for both CMESP and CDOPTP are based on branch-and-bound methods. We extend a spectral upper-bounding method for the CMESP to the GCMESP.

We propose an infeasible interior-point algorithm for constrained linear least-squares problems based on the primal-dual regularization of convex programs of Friedlander and Orban. Regularization allows us to dispense with the assumption that the active gradients are linearly independent. At each iteration, a linear system with a symmetric quasi-definite (SQD) matrix is solved. This matrix is shown

Portfolio selection is recognized as the birth-place of modern finance. Weighted-sums methods or e-constraint methods are normally utilized for portfolio optimization, but the results are only approximations of efficient frontiers. One concern of portfolio selection is efficiency-diversification discrepancies that efficient frontiers lack diversification. Scholars typically analyze the discrepancies

To cater to the growing personalized need of customers, increasingly more make-to-order distribution centers consider a two-phase production (i.e. raw material granulation and order packaging) process when making production and routing decisions, especially for time-sensitive commodities. In this article, we extend the production routing problem to the make-pack-route problem (MPRP) to devise production