Omega-international Journal of Management Science最新文献

{"title":"An exact scenario-independent deterministic equivalent form of stochastic programs embedding Multivariate Extreme Value discrete choice problems","authors":"Michel Bierlaire ,&nbsp;Edoardo Fadda ,&nbsp;Lohic Fotio Tiotsop ,&nbsp;Daniele Manerba","doi":"10.1016/j.omega.2026.103514","DOIUrl":"10.1016/j.omega.2026.103514","url":null,"abstract":"<div><div>We address the class of two-stage Stochastic Programs embedding, in their second stage, a set of Discrete Choice Problems (tsSP-DCPs), one independent from the other, but all linked by the first-stage decisions This decisional structure can be found within many managerial and organizational contexts in relation to several applications such as location–allocation, routing, scheduling, and sequencing. Generally, solving a two-stage stochastic program requires the analytical derivation of the second-stage problem’s expected optimum, which in turn implies calculating a multidimensional integral. Therefore, a common practice is approximating the random variables involved through a finite set of scenarios and solving a huge scenario-dependent program, which affects the scalability of making optimal decisions under uncertainty. However, under some assumptions commonly adopted in the discrete choice context, we can prove that a closed-form analytical expression of the expected second-stage optimum of a tsSP-DCP can be derived, and an exact scenario-independent equivalent deterministic program can be obtained. Through a numerical showcase, we validate our approach in terms of efficiency and effectiveness. Our equivalent deterministic form, which only requires estimating a few parameters in practice, is far less computationally demanding than any scenario-based deterministic equivalent forms, thereby simplifying the decision-making process. Finally, we show that our methodology can be generalized to address a larger class of two-stage stochastic programs, i.e., those in which the second-stage expected optimum is decomposable into a finite number of expectations of Extreme Values and in which second-stage utilities may also depend on first-stage decisions.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"142 ","pages":"Article 103514"},"PeriodicalIF":7.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User ecology: The optimal ecology construction and product upgrade strategies","authors":"Yusheng Wang ,&nbsp;Yongjian Li ,&nbsp;Fangchao Xu","doi":"10.1016/j.omega.2025.103511","DOIUrl":"10.1016/j.omega.2025.103511","url":null,"abstract":"<div><div>Firms are now promoting interactions among users by constructing user ecology, thereby fostering a intra-user network effect to enhance the value proposition of their products. However, compatibility, a pivotal attribute of such ecology, may potentially transform this potent network effect into a double-edged sword, particularly from the upgrade perspective. This study develops a stylized model to explore the interplay between upgrade strategy and user ecology construction. Initially, we analyze the optimal upgrade strategies for firms, distinguishing between those with no/partial/comprehensive user ecology. Subsequently, we carry out the analysis of the optimal design for the user ecology. Moreover, we explore the effectiveness of strategically disposing of partial ecology. The primary findings illustrate the importance of upgrade costs in scenarios without user ecology, where the line-extension strategy dominants the replacement strategy. In the presence of user ecology, we elucidate the demand aggregation effect that may hinder users from buying a new-generation product. Consequently, the replacement strategy emerges as optimal when product differentiation is low. Intriguingly, the existence of user ecology may impede firms from introducing new-generation products. The construction of user ecology provides advantages for firms in emerging markets but may be detrimental in mature markets. Furthermore, our results highlight that comprehensive user ecology may compromise firm’s profit. Disposing of partial ecology strategically can enhance performance, especially when both network effect and product differentiation are low. Lastly, we further investigate the impact of repeat purchases, proportion of new users, and compatibility of the ecology on the main results.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103511"},"PeriodicalIF":7.2,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective electric vehicle charging scheduling under stochastic duration uncertainty","authors":"Aimen Khiar ,&nbsp;Mohamed el Amine Brahmia ,&nbsp;Ammar Oulamara ,&nbsp;Lhassane Idoumghar","doi":"10.1016/j.omega.2025.103506","DOIUrl":"10.1016/j.omega.2025.103506","url":null,"abstract":"<div><div>The ongoing electrification of the transport sector, driven by the numerous advantages of electric vehicles (EVs), introduces new challenges related to charging logistics, particularly due to long charging durations and uncertain conditions, posing significant negative impacts on grid stability and user satisfaction. While existing literature on EV charging scheduling often assumes deterministic charging durations, real-world conditions introduce randomness due to uncontrollable factors such as battery state-of-charge (SoC), fluctuating grid demand, and ambient temperature. In this paper, we address the <em>Electric Vehicle Charging Scheduling Problem</em> (EVCSP) under uncertain charging durations. First, we introduce a novel, flexible multi-objective scheduling model operating on a continuous time horizon, considering stochastic charging durations and incorporating controlled preemptions during charging, where the non-preemptive mode is a particular case. Then, we prove that finding a feasible assignment of EVs to chargers is strongly NP-hard under this uncertainty, even assuming identical chargers. Our model accounts for realistic constraints, including heterogeneous charger power levels and vehicle-charger compatibility, aiming to minimize the conditional expected values of grid overload and total tardiness, while also minimizing the undelivered energy to users. Given the problem’s computational complexity, we adapt four evolutionary algorithms (EAs), namely, extensions of the Non-Dominated Sorting Genetic Algorithm (NSGA), namely NSGA-II and NSGA-III, alongside other state-of-the-art multi-objective metaheuristics, including the Multi-Objective Cuckoo Search (MOCS) algorithm, and the Multi-Objective Grey Wolf Optimizer (MOGWO) by defining problem-specific operators to explore the search space and efficiently approximate the optimal Pareto front. Assuming lognormally distributed charging durations, we conducted a comparative experimental analysis on real-world data to evaluate the four methods and revealed that MOCS algorithm outperforms the other competitors.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103506"},"PeriodicalIF":7.2,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating stochastic optional pickup demand in routing operations with divisible services for hub-and-spoke e-commerce returns management systems","authors":"Alessandro Gobbi ,&nbsp;Daniele Manerba ,&nbsp;Francesca Vocaturo","doi":"10.1016/j.omega.2025.103510","DOIUrl":"10.1016/j.omega.2025.103510","url":null,"abstract":"<div><div>Nowadays, e-commerce is associated with many returns due to emotional consumption, information asymmetry, factory defects, or, more generally, customer dissatisfaction. However, little attention has been paid to reverse logistics in the e-commerce industry, although it has been proven crucial to improving the perceived quality of service and profit revenue. Depending on the nature of the goods, one successful option is to design combined <em>forward-and-reverse</em> logistics systems, where the collection of returns is ensured along with the traditional distribution of products, together with <em>hub-and-spoke</em> networks in which both distribution and collection demand from many spokes are aggregated into a few hubs. In this context, we study a variant of the vehicle routing problem with divisible deliveries and pickups, in which each hub may be associated with a mandatory delivery demand and a mandatory return pickup demand, and it may be visited more than once within the same or different routes. To address realistic scenarios, and given the large fluctuation of demand within the aggregating hubs, we also assume that an uncertain optional pickup quantity may arise and formulate the problem through two-stage Stochastic Programming, proposing and modeling ad-hoc recourse actions. Moreover, an integer L-shaped method enhanced with ad-hoc valid inequalities is developed for solving the resulting problem. Managerial insights on the underlying tactical and operational policies are inferred from extensive computational experiments on a case study and on realistic artificial instances.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103510"},"PeriodicalIF":7.2,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavior-Based Pricing strategy of quality-differentiated products with imperfect customer recognition capability","authors":"Tao Jiang ,&nbsp;Kaigeng Shen ,&nbsp;Youwei Guo ,&nbsp;Lei Guan","doi":"10.1016/j.omega.2025.103488","DOIUrl":"10.1016/j.omega.2025.103488","url":null,"abstract":"<div><div>The development of data technology has enabled firms to identify and analyze consumers’ purchase history and classify them into new and old customers for price discrimination. However, this type of price discrimination tends to cause customer dissatisfaction and lead to resistance against firms’ data-driven pricing practices. Consequently, it challenges firms’ customer recognition capability. This paper develops a two-period pricing model in which two firms, differing in product quality, investigate the impact of behavior-based pricing (BBP) on firms with varying quality levels when they possess imperfect customer recognition capability. We find, first, that imperfect customer recognition capability causes different effects on price in each period for firms of different quality, depending on the level of product quality differentiation. Second, quality advantages do not always lead to more markets for high-quality firms; low-quality firms are also in a position to gain more markets. Third, due to firms’ customer recognition capability and quality differentiation, when both firms adopt BBP, they will both achieve higher profits and reach a ”win–win” situation. Conversely, if only one firm adopts BBP, it will result in reduced profitability for both firms, leading to a ”lose–lose” scenario. Finally, we have examined consumer surplus and social welfare, and the findings provide a theoretical foundation and policy recommendations for governments to develop regulatory measures against price discrimination in the digital economy era.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103488"},"PeriodicalIF":7.2,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimization with order acceptance for the cumulative job shop scheduling problem in agribusiness","authors":"Florian Linß ,&nbsp;Mike Hewitt ,&nbsp;Janis S. Neufeld ,&nbsp;Udo Buscher","doi":"10.1016/j.omega.2025.103504","DOIUrl":"10.1016/j.omega.2025.103504","url":null,"abstract":"<div><div>Developing new crop species is crucial for addressing global food challenges and improving agricultural efficiency. In agribusiness, this process involves systematically growing and assessing numerous crop variants under controlled conditions to determine their yield potential and adaptability. Formally, this is a job shop scheduling problem because the crops can be understood as jobs that may have different processing sequences on the resources (e.g., greenhouses). However, since the resources can process several jobs simultaneously, a cumulative job shop problem arises. The primary objective is to maximize the number of accepted jobs from a job pool with given release and due dates. The secondary objective is to minimize delays in job processing, i.e., the jobs’ waiting times, as earlier completion of jobs allows for faster feedback and refinement of future crop variants, ultimately improving the overall testing and development process. In this paper, we formulate this problem as a mixed integer and constraint programming problem. We also show how it can be solved with a flexible hierarchical approach, even for very large problem instances. Comprehensive computational experiments first show that available machine capacity has a greater influence on the objectives than the length of the processing time windows, resulting from the difference between the due and release dates. Secondly, a deviation from the maximum number of accepted jobs disproportionately reduces delays.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103504"},"PeriodicalIF":7.2,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feature-based profitability evaluation for newsvendor-type products","authors":"Yuying Zhang,&nbsp;Shiming Deng,&nbsp;Wanpeng Wang","doi":"10.1016/j.omega.2025.103508","DOIUrl":"10.1016/j.omega.2025.103508","url":null,"abstract":"<div><div>We study how firms selling newsvendor-type products determine order quantities to maximize the probability of achieving a target profit, referred to as profitability. Unlike existing literature, we assume decision-makers have access to historical demand data and related feature data. To integrate feature information into the optimization model, we propose a weighted sample average approximation method that resolves the inherent inconsistency of traditional SAA approaches. This feature-based model is reformulated as a mixed integer programming for efficient solution. We further prove the consistency and asymptotic optimality of the ordering policy derived from our method. For high-dimensional feature settings with irrelevant features, we develop a decision-based feature selection method within the nonparametric optimization framework. Additionally, we introduce a nonparametric bootstrap method to estimate conservative profitability, mitigating overestimation risks caused by sampling errors. Numerical experiments using both synthetic and real data are conducted to demonstrate the effectiveness of our proposed methods. Notably, as the sample size increases, our feature selection method consistently identifies all relevant features, meaning the probability of correctly selecting the model approaches 1. Furthermore, in real-data experiments, our feature-based method improves profitability by more than 50% compared to the SAA method.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103508"},"PeriodicalIF":7.2,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The stochastic production routing problem with adaptive routing and service level constraints","authors":"Ali Kermani,&nbsp;Jean-François Cordeau,&nbsp;Raf Jans","doi":"10.1016/j.omega.2025.103496","DOIUrl":"10.1016/j.omega.2025.103496","url":null,"abstract":"<div><div>Demand uncertainty poses a challenge to most companies in manufacturing and services as it can lead to significant profit losses if not addressed properly. To deal with this risk, companies may adopt specific service level targets to satisfy at least a certain proportion of their demand while considering operational constraints and minimizing the total cost. In this study we address the stochastic production routing problem (PRP) with adaptive routing and service level constraints. The PRP unifies the production, inventory and routing decisions into an integrated problem aimed at improving coordination across different parts of the system. We consider four different types of service levels, where each type uses a specific metric based on assumptions aligning with the needs of the company. These metrics encompass aspects such as the occurrence of stockouts or allowed ratios of backlogs or backorders to average demand. A two-stage stochastic formulation is proposed for each type of service level. Setup decisions are made in the first stage, and production, inventory, and routing decisions are adapted after demand realization. Considering routing decisions in the second stage increases flexibility while lowering overall costs. However, the resulting optimization problem is more challenging to solve than the case where routing decisions are made in the first stage. To address this issue, we introduce an iterative matheuristic algorithm designed to yield high-quality solutions within a reasonable computation time. The effectiveness of the proposed heuristic algorithm is demonstrated through extensive experiments, highlighting its potential to assist companies in managing demand uncertainty and enhancing operational efficiency.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103496"},"PeriodicalIF":7.2,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecosystem risk management: A MIP approach to spatial prioritization of multiple management actions","authors":"Matías Moreno-Faguett ,&nbsp;José Salgado-Rojas ,&nbsp;Virgilio Hermoso ,&nbsp;María José Martínez-Harms ,&nbsp;Bárbara Larraín-Barrios ,&nbsp;Eduardo Álvarez-Miranda","doi":"10.1016/j.omega.2025.103507","DOIUrl":"10.1016/j.omega.2025.103507","url":null,"abstract":"<div><div>Healthy ecosystems are essential for conserving biodiversity and supporting human well-being, yet human activities impose significant pressures, risking ecological features such as species, habitats and ecosystem services. While Systematic Conservation Planning (SCP) has been widely used to address these issues, traditional approaches often result in risk-averse solutions, focusing management efforts on low-impact sites and potentially leading to suboptimal conservation outcomes. To address this gap, we propose a mixed-integer programming (MIP) approach designed to explicitly reduce ecosystem risk by prioritizing cost-effective actions and sites to manage multiple stressors, while accounting for spatial needs such as connectivity and socio-political boundaries. Our framework integrates a state-of-the-art ecological risk assessment tool (InVEST-Habitat Risk Assessment) with an SCP-based mathematical programming tool (<span>prioriactions</span> <em>R</em> package) for guiding risk management. We applied this framework to Chilean Patagonia, using giant kelp (<em>Macrocystis pyrifera</em>) forests as a proxy for coastal ecosystems under pressure from stressors such as aquaculture, vessel activities, and ocean temperatures. The framework was assessed across five planning scenarios, each with different spatial needs, and was compared with traditional approaches. The results demonstrated that our approach consistently outperforms traditional ones, ensuring risk reduction in all scenarios. In key comparisons, the traditional approaches failed to exceed 47% of the risk reduction target. In addition to meeting higher risk reductions, our approach successfully overcame spatial needs in all scenarios. However, the inclusion of these constraints increased computational difficulty by 36 to 150 times and solution costs by up to 71%. These findings highlight the flexibility of the framework, but also emphasize the need for coordinated planning. This work aims to bridge the gap between risk assessment and risk management in conservation planning by explicitly incorporating risk as a primary objective instead of a secondary outcome. Our framework is applicable to any multi-stressor context, providing a flexible tool for designing cost-effective management strategies. By focusing on risk reduction and incorporating spatial needs, this approach enhances long-term ecosystem resilience.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"142 ","pages":"Article 103507"},"PeriodicalIF":7.2,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint scheduling policy for volunteers and materials in multi-organizational disaster response","authors":"Bo Feng,&nbsp;Qingchun Meng,&nbsp;Guodong Yu","doi":"10.1016/j.omega.2025.103505","DOIUrl":"10.1016/j.omega.2025.103505","url":null,"abstract":"<div><div>In disaster response, logistics management requires efficient matching among workforce, materials and tasks. Uncertain and non-stationary task arrivals, heterogeneity in workforce skill levels and uncertainty in task execution times, together with the need to coordinate materials with workforce deployment, jointly render the disaster response process highly stochastic; meanwhile, multi-organizational participation further introduces cross-organizational resource coordination challenges. Existing approaches struggle to address these jointly—stochastic demand, cross-organizational coordination, and inefficiencies from decoupled workforce–material scheduling—and often require frequent manual retuning that limits responsiveness and scale. We develop an adaptive, cross-organizational decision system that co-optimizes volunteer assignment, material allocation, and replenishment in real time. System evolution is governed by task arrivals, service completions, and inventory decay, while assignment, material allocation, and replenishment act directly on these drivers. We adopt a Markov Decision Process (MDP) framework to integrate multi-organizational collaboration, real-time resource management and task allocation, and implement an end-to-end controller via hierarchical deep reinforcement learning(HDRL) that jointly optimizes volunteer assignment, material allocation, and replenishment. Across varied demand regimes, scales, and perishability levels, the proposed joint controller consistently outperforms common queueing heuristics: task backlogs decrease by about 30–85% and personnel costs by 16–42%, while logistics and resource-usage costs remain broadly comparable, with occasional modest logistics increases that relieve congestion. Relative to short-horizon rolling dynamic programming, it achieves lower backlog and total cost with less manual re-tuning, millisecond-level inference latency, and smooth scaling.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"141 ","pages":"Article 103505"},"PeriodicalIF":7.2,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}