International Transactions in Operational Research

Publisher:: Wiley
Publication date:: 2021-02-01

ISBN:: 0969-6016

Issue Number

No. 31-2, March 2024

Latest documents

An analysis of price strategies with price matching in the presence of showrooming
With multi‐channel retail competition, some offline retailers implement price matching services to combat consumers’ showrooming behavior. With this service, offline retailers cut their prices to match the online price if it is lower. In this paper, we establish a game model that involves an offline and online retailer in the presence of showrooming to analyze the impact of price matching. Specifically, we capture consumers’ uncertainty of product value and heterogeneous awareness of price matching and assume that the online retailer provides a free return policy. The results indicate that price matching alleviates showrooming and relaxes competition. Moreover, we find that the online retailer adopts a randomized pricing strategy if the offline visiting cost is moderate. We further show that the price matching strategy does not necessarily benefit offline retailers and hurt online retailers. Subsequently, we identify the offline retailers’ optimal conditions for implementing price matching.
An optimization method for characterizing two groups of data
Feature selection aims to choose a subset of features, out of the set of candidate features, such that the selected set best represents the whole in a particular aspect. We propose an optimization model for the problem of selecting features in the presence of two groups of data. The objectives include minimizing the number of selected features and maximizing similarities within the same group and differences between different groups. We use the lexicographic method and prove several properties of the problem. We show that obtaining even feasible solutions for the problem can be challenging. Therefore, we propose matheuristic algorithms. We test our algorithms on both randomly generated and real‐world datasets. The computational results indicate that the proposed matheuristics deliver quality solutions in a reasonable amount of time.
Research on entropy weight multiple criteria decision‐making evaluation of metro network vulnerability
When the subway network system has insufficient resilience and strong vulnerability, the network operation function will be greatly attenuated or even lost due to the failure of key nodes or lines. Evaluating the vulnerability of the metro network is one of the keys to prevent and control risks. This paper proposes an entropy weight multiple criteria decision‐making evaluation method that combines the vulnerability indexes of agglomeration, network efficiency, and network traffic with the multiple criteria decision‐making method, classifies the vulnerability of subway stations with a clustering idea, and analyzes the most vulnerable area of the Beijing Metro network with the Newman fast algorithm. The results show that this method can evaluate the node vulnerability of metro networks more accurately and effectively by considering the topological vulnerability, functional vulnerability, and human flow function vulnerability of the networks. According to the node vulnerability value, the stations can be divided into five grades: The station at the intersection of the loop and radial lines and its adjacent stations have a higher vulnerability level. The vulnerability level of the downtown core area and suburban line terminal stations is relatively low, and the areas with the greatest vulnerability of the Beijing Metro network are mainly located on the east and west sides of the core city.
Optimal ordering decisions for an omnichannel retailer with ship‐to‐store and ship‐from‐store
Many retailers have recently integrated online and offline channels to give consumers a seamless shopping experience. Our study considers an omnichannel retailer fulfilling order delivery by adopting two common strategies, ship‐to‐store (STS) and ship‐from‐store (SFS), when one of the channels is in short supply. We develop a newsvendor model to investigate the effects of these two omnichannel fulfillment strategies on the retailer's order decisions and expected profits. The analysis reveals the key roles of the external market and inventory cost of different channels in adopting an omnichannel strategy. An interesting finding is that the retailer may adopt the STS (SFS) strategy and take the offline (online) channel as a showroom (virtual webroom) to obtain higher profits than without adopting an omnichannel strategy.
Disposable or reusable? Packaging strategy and pricing decision for fresh food considering environmental policies
Packaging has become an important concern of fresh food supply chains and will exert a growing influence under environmental policies. In this paper, we have discussed three specific issues to investigate fresh food supply chains’ packaging strategy, that is, whether to use disposable packaging containers (DPCs) or reusable packaging containers (RPCs), whether to purchase or rent RPCs, and the influences of environmental policies. Our research has generated some key findings. First, we find that penalty (such as taxes) and reward (such as subsidies) are simultaneously needed to motivate supply chains to choose RPCs. In terms of the “purchasing or renting” choice, it highly depends on the relative magnitude of the purchase and rental subsidies, along with the number of uses of RPCs and the perishability of fresh food. We also conclude that reusing RPCs for more times has two‐sided effects, that is, the effect of cost saving and the effect of accelerated deterioration. Thus, it is not recommended to excessively reuse RPCs. In addition, we make two extensions. First, we consider endogenous tax rate and subsidy rates and discuss from the perspective of social welfare. Second, we consider endogenous sales price and rental price of RPCs and study the optimal decisions of the RPC operator. Results show that the government should establish a classified tax and subsidy system for packaging containers, and meanwhile benchmarking prices for RPC services should be set to curb the RPC operator's free‐riding behavior.
A branch‐and‐price‐based heuristic for the vehicle routing problem with two‐dimensional loading constraints and time windows
Addressed in this study is a vehicle routing problem with two‐dimensional loading constraints and time windows (2L‐CVRPTW), aiming to minimize the transportation cost while satisfying the two‐dimensional loading and routing constraints with time windows. To solve this problem, for the first time a mixed‐integer linear programming model is formulated with considering practical last‐in‐first‐out loading constraints, and a branch‐and‐price‐based (BP‐based) heuristic is proposed based on a set partitioning formulation. In the heuristic, a modified labeling algorithm is proposed for the complex pricing problem, which is a relaxation of the elementary shortest path problem with resource constraints and two‐dimensional loading constraints. Therein, an effective Tabu‐maximum open space packing heuristic is proposed to verify the feasibility of the two‐dimensional packing problem of each route generated by the labeling algorithm. In addition, effective accelerating and branching strategies are introduced to improve the solving efficiency of the heuristic. To evaluate the effectiveness and the advantages of the proposed heuristic, extensive computational experiments are performed based on the generated instances. The computational results show that the proposed BP‐based heuristic can effectively solve the 2L‐CVRPTW, in which the optimal solutions can be achieved much faster than CPLEX in small‐scale problems. Relationships between the transportation cost and the characteristics of the instances are analyzed. The stability of the algorithm and the effectiveness of the accelerating strategies are verified and discussed.
The impact of production diseconomies on manufacturer encroachment
We consider a supply chain with a manufacturer and a retailer, where the manufacturer is diseconomy of scale regarding production and may encroach into the downstream market. We prove that the production diseconomy changes the traditional wisdom regarding the impact of manufacturer encroachment on supply chain performance. First, we show that the production diseconomy disincentivizes the manufacturer's encroachment. Second, different from the literature that believes retailer can be better off as long as it has a selling cost advantage compared with the manufacturer, we establish the condition where encroachment always hurts the retailer regardless of the selling cost advantage. Third, we find that when the price does not respond sensitively to the quantity, an encroaching manufacturer would increase the wholesale price. Surprisingly, the supply chain's profit still could increase. Finally, we check how the retail competition, imperfect substitution, and price competition affect the corresponding results shown above. We show that the retail competition disincentivizes the manufacturer's encroachment and weakens the whole industry's profit benefit from the encroachment. In contrast, imperfect substitution increases the manufacturer's encroachment incentives and strengthens the industry's profit benefit from the encroachment. In the case of imperfect substitution with quantity competition, the consumers might be worse off after the manufacturer encroaches; otherwise, they benefit from the manufacturer's encroachment.
Supply chain coordination with financial constraints considering delivery time and cross‐channel spillover effect
A manufacturer selling its products via an offline channel and a capital‐constrained platform is considered in our work. The agency or reseller mode is operated by the platform. Affected by the delivery time, the offline demand is affected by the online channel, which is called the cross‐channel spillover effect (CCSE). Building game models for analysis, we derive the following major results: First, how the commission rate affects the optimal production quantity depends on CCSE. CCSE has no impact on (decreases) the platform's optimal delivery time in the agency (reseller) mode. Besides, the platform's optimal profit decreases with a positive CCSE but increases with a negative CCSE in the agency mode. But in the reseller mode, it always increases with CCSE. Second, the financial constraint decreases the optimal production quantity and extends the optimal delivery time. Third, the agency mode always leads to a larger market share and longer delivery time than the reseller mode. The manufacturer should choose the reseller mode (agency mode) under a high (low) slotting fee. Last, the manufacturer and platform cannot realize coordination by using only the agency or reseller mode. However, considering the manufacturer‐led Stackelberg game, the reseller mode can do so, while the agency mode cannot. Further, considering a retailer and a third party under the omnichannel strategy, the reseller mode can always coordinate them, and the agency mode can only do so at a low interest rate of the loan.
An extended model of coordination of an all‐terrain vehicle and a multivisit drone
In this paper, a model that combines the movement of a multivisit drone with a limited endurance and a base vehicle that can move freely in the continuous space is considered. The mothership is used to charge the battery of the drone, whereas the drone performs the task of visiting multiple targets of distinct shapes: points and polygonal chains. For polygonal chains, it is required to traverse a given fraction of its lengths that represent surveillance/inspection activities. The goal of the problem is to minimize the overall weighted distance traveled by both vehicles. A mixed integer second‐order cone program is developed and strengthened using valid inequalities and giving good bounds for the Big‐M constants that appear in the model. A refined matheuristic that provides reasonable solutions in short computing time is also established. The quality of the solutions provided by both approaches is compared and analyzed on an extensive battery of instances with different number and shapes of targets, which shows the usefulness of our approach and its applicability in different situations.
The efficacy of utility functions for multicriteria hospital case‐mix planning
A new approach to perform hospital case‐mix planning (CMP) is introduced in this article. Our multicriteria approach utilizes utility functions (UF) to articulate the preferences and standpoint of independent decision makers regarding outputs. The primary aim of this article is to test whether a utility functions method (UFM) based on the scalarization of aforesaid UF is an appropriate quantitative technique to (i) distribute hospital resources to different operating units and (ii) provide a better capacity allocation and case mix. Our approach is motivated by the need to provide a method able to evaluate the trade‐off between different stakeholders and objectives of hospitals. To the best of our knowledge, no such approach has been considered before in the literature. As we will later show, this idea addresses various technical limitations, weaknesses, and flaws in current CMP. The efficacy of the aforesaid approach is tested on a case study of a large tertiary hospital. Currently UF are not used by hospital managers, and real functions are unavailable, hence, 14 rational options are tested. Our exploratory analysis has provided important guidelines for the application of these UF. It indicates that these UF provide a valuable starting point for planners, managers, and executives of hospitals to impose their goals and aspirations. In conclusion, our approach may be better at identifying case mix that users want to treat and seems more capable of modeling the varying importance of different levels of output. Apart from finding desirable case mixes to consider, the approach can provide important insights via a sensitivity analysis of the parameters of each UF.