Annals of Operations Research

Akbay, Mehmet Anıl; Blum, Christian; Kalayci, Can Berk

doi: 10.1007/s10479-024-06295-9pmid: N/A

Many packing, routing, and knapsack problems can be expressed in terms of integer linear programming models based on set covering. These models have been exploited in a range of successful heuristics and exact techniques for tackling such problems. In this paper, we show that integer linear programming models based on set covering can be very useful for their use within an algorithm called “Construct, Merge, Solve & Adapt”(CMSA), which is a recent hybrid metaheuristic for solving combinatorial optimization problems. This is because most existing applications of CMSA are characterized by the use of an integer programming solver for solving reduced problem instances at each iteration. We present applications of CMSA to the variable-sized bin packing problem and to the electric vehicle routing problem with time windows and simultaneous pickups and deliveries. In both applications, CMSA based on a set covering model strongly outperforms CMSA when using an assignment-type model. Moreover, state-of-the-art results are obtained for both considered optimization problems.

Badri, Hossein; Bahreini, Tayebeh; Grosu, Daniel

doi: 10.1007/s10479-024-06329-2pmid: N/A

The flow shop scheduling problem is one of the most complex and widely applicable scheduling problem. In this paper, we design efficient parallel algorithms for solving large-size non-permutation flow shop scheduling problems by leveraging the huge amount of computing power of the current multi-core computing systems. We design two parallel algorithms based on the Shifting Bottleneck heuristic. The first one is a coarse-grained parallel algorithm that is suitable for execution on multi-core systems with a small number of cores, while the second one is a fine-grained parallel algorithm suitable for multi-core systems with a large number of cores. We perform an extensive experimental analysis to evaluate the performance of the proposed algorithms for instances of various sizes. The results show that the proposed algorithms can solve large-size instances of the problem in a reasonable amount of time and obtain solutions that are within acceptable distance from the lower bounds. The proposed parallel algorithms achieve good speedup with respect to the serial variants of the algorithms.

Brudner, Amir; Gavious, Arieh

doi: 10.1007/s10479-024-06232-wpmid: N/A

Academic institutions seek to enhance their reputation, which is one of their primary assets. Doing so requires a massive investment of resources in research, recruiting a high-quality academic staff, and building campuses and state-of-the-art laboratories. To obtain the necessary financial resources, institutions must attract students, donors, and government budgets and grants. This paper introduces a stylized dynamic model demonstrating how an institution can best allocate its resources between teaching and research. We create a simulated competition that resembles the real situation where the enhancement of the institution’s reputation depends not only on its resource allocation but also on its competitors’ actions and reputation. We consider a two-institution contest over time using a differential game solution with open-loop strategies. In this case, the steady-state investment in research increases and the level of teaching decreases.

Chen, Quanpeng; Chen, Xiaogang; Li, Shu; Chen, Jun

doi: 10.1007/s10479-024-06320-xpmid: N/A

Small and medium enterprises (SMEs) in supply chains often struggle to obtain external financial resources from banks, due to their poor supply chain visibility. Prior studies suggest that adopting blockchain technology can enhance supply chain visibility, thus facilitating access to supply chain finance (SCF). In this study, we compare the traditional SCF mode with the blockchain-enabled SCF mode within the framework of a dual-channel closed-loop supply chain (CLSC). Our analysis incorporates both prepayment financing and accounts receivable financing or purchase order financing into the analytical model. Our main findings are as follows. Firstly, adopting blockchain technology leads to a reduction in the interest rate, enabling the manufacturer and the retailer to raise their buy-back prices. This increase in buy-back prices subsequently encourages greater recycling of used products. Secondly, in a context marked by high cross-price elasticity, we observe abrupt pricing fluctuations in both online and offline sales channels. However, adopting blockchain technology can effectively mitigates these fluctuations, thus ensuring the sustained stability of demand in both sales channels. Thirdly, in the blockchain-enabled mode, equilibrium wholesale price, offline sales price, manufacturer’s buy-back price, and retailer’s buy-back price are higher compared to those in the traditional mode. Conversely, the equilibrium direct sales price is lower in the blockchain-enabled mode than in the traditional mode. Fourthly, changes in interest rates and cross-price elasticity have analogous impacts on pricing dynamics in both the traditional and blockchain-enabled modes. Fifthly, adopting blockchain technology leads to an all-win outcome for participants in SCF arrangements only when the benefits of blockchain-enabled traceability and reduced interest rates outweigh the costs associated with hosting and access.

da Silva, Renan F. F.; Borges, Yulle G. F.; Schouery, Rafael C. S.

doi: 10.1007/s10479-024-06323-8pmid: N/A

The Colored bin packing problem (CBPP) is a generalization of the Bin packing problem (BPP). The CBPP consists of packing a set of items, each with a weight and a color, in bins of limited capacity, minimizing the number of used bins and satisfying the constraint that two items of the same color cannot be packed side by side in the same bin. In this article, we proposed an adaptation of BPP heuristics and new heuristics for the CBPP. Moreover, we propose a set of fast neighborhood search algorithms for CBPP. These neighborhoods are applied in a meta-heuristic approach based on the Variable neighborhood search (VNS) and a matheuristic approach that combines linear programming with the meta-heuristics VNS and Greedy randomized adaptive search (GRASP). The results indicate that our matheuristic is superior to VNS and that both approaches can find near-optimal solutions for a large number of instances, even for those with many items.

Daskin, Mark S.; Redmond, Michael; Levin, Abigail

doi: 10.1007/s10479-024-06276-ypmid: N/A

We introduce a multi-objective variant of the newsvendor problem in which we maximize the expected profit and minimize the maximum regret associated with the decision of how many items to procure from a supplier in the face of unknown demand. When the demand distribution is bounded, the problem is relatively simple. With an unbounded demand distribution, the maximum regret is undefined. In that case, we introduce a chance-constrained variant of the model in which we minimize the maximum regret over a range of demand values whose probability is at least a user-specified value, γ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\gamma$$\end{document}. We provide an algorithm for finding the tradeoff between the expected profit and the γ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\gamma$$\end{document}-level maximum regret. We also show that, when operating near the optimal single-objective newsvendor solution, we can significantly reduce the γ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\gamma$$\end{document}-level maximum regret with little degradation in the expected profit.

Drezner, Nethanel; Barron, Yonit

doi: 10.1007/s10479-024-06261-5pmid: N/A

This paper studies a continuous-review inventory replenishment model with a limited storage capacity S in an uncertain environment. We assume that the demands and returns follow independent Poisson processes. We further assume a ra1079 shelf life, a random lead time, and early loss. The storage is managed according to the base-stock (S, s) policy for s<S,S>0.\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$s<S,S>0.$$\end{document} In case of overstock, each returned item exceeding S is transferred to a foreign facility. If during the lead time a demand reaches zero stock, we consider two alternatives: either allow partial backordering up to LB\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_{B}$$\end{document} items, beyond which the unsatisfied demand is lost, or call for an immediate and costly emergency supply up to level 0<QBe≤S\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$0<Q_{B}^{e}\le S$$\end{document}. Our objective is to study how the thresholds s,  S,  LB,\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_{B},$$\end{document} and QBe\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$Q_{B}^{e}$$\end{document} are impacted by the system’s parameters, such as returns, demands, and costs. Using a Markovian framework, we derive the steady-state probabilities for the inventory level, and construct closed-form expressions for the average cost functions. Then, we numerically investigate the impact of the different parameters on the best policy and on the threshold levels. We compare the two alternatives and identify situations in which calling for an emergency supply is economically profitable.

Geiger, Gebhard

doi: 10.1007/s10479-024-06259-zpmid: N/A

The paper develops a conceptual framework for the analysis and management of catastrophic risk. The framework serves to assess rare extreme events in systematic, quantitative and consistent ways. It dispenses with probabilistic extreme value theory, concentrating on descriptive statistics and simple probability distributions. Risk assessment is based on a recently developed axiomatic approach to non-expected utility preferences defined on the set of risky alternative courses of action available to an agent. The utility values of catastrophic risks are given an explicit algebraic representation, which shows them to be highly unstable (“elastic”) in the sense that they respond disproportionately to small perturbations of the decision outcomes and their probabilities. Various elasticity coefficients are defined for the outcome variables and utility preferences attached to them. They indicate whether a variable possibly takes on large negative values. The coefficients can also be defined as sample statistics and, thus, computed from observed data. The approach admits various applications to practical problems of disaster risk management. The applications include estimations of the effectiveness and cost-efficiency of risk management, the specification of limits of acceptance of catastrophic risk for regulatory purposes, and safety and security systems design and dimensioning.

Geng, Shaoqing; Gong, Yu; Hou, Hanping; Yang, Jianliang; Onggo, Bhakti Stephan

doi: 10.1007/s10479-024-06324-7pmid: N/A

Disasters cause huge economic losses, affect the lives of many people, and severely damage the environment. Effective resource management during disaster preparedness and response phases improves distribution efforts and service levels and, hence, accelerates the disaster relief operations. Resource management in response to catastrophe has received increasing research attention in recent years, but no review paper focuses on this specific topic. Thus, the main purpose of this paper is to review the existing literature on resource management for disaster relief published in English in peer-reviewed journals in order to fill the gap. We apply bibliometric, network, and content analyses in our review to identify popular research topics, classify the literature into research clusters, and analyze the interrelationships between these research clusters. The second purpose of this paper is to identify gaps and trends in existing research. Finally, we propose six future research directions that provide a roadmap for resource management research for disaster relief.

Gök, S. Zeynep Alparslan; Brink, René van den; Palancı, Osman

doi: 10.1007/s10479-024-06265-1pmid: N/A

Standard solutions for cooperative transferable utility (TU-) games assign to every player in a TU-game a real number representing the player’s payoff. In this paper, we introduce interval solutions for TU-games which assign to every player in a game a payoff interval. Even when the worths of coalitions are known, it might be that the individual payoff of a player is not known. According to an interval solution, every player knows at least a lower- and upper bound for its individual payoff. Therefore, interval solutions are useful when there is uncertainty about the payoff allocation even when the worths that can be earned by coalitions are known. Specifically, we consider two interval generalizations of the famous Shapley value that are based on marginal contributions in terms of intervals. To determine these marginal interval contributions, we apply the subtraction operator of Moore. We provide axiomatizations for the class of totally positive TU-games. We also show how these axiomatizations can be used to extend any linear TU-game solution to an interval solution. Finally, we illustrate these interval solutions by applying them to sequencing games.