Annals of Operations Research

El Ouardighi, Fouad; Khmelnitsky, Eugene; Leandri, Marc

doi: 10.1007/s10479-020-03638-0pmid: N/A

An important yet largely unexamined issue is how the interaction between deforestation and pollution affects economic and environmental sustainability.This article seeks to bridge the gap by introducing a dynamic model of pollution accumulation where polluting emissions can be mitigated and the absorption efficiency of pollution sinks can be restored. We assume that emissions are due to a production activity, and we include deforestation both as an additional source of emissions and as a cause of the exhaustion of environmental absorption efficiency. To account for the fact that the switching of natural sinks to a pollution source can be either possible, and in such a case even reversible, or impossible, we consider that restoration efforts can be either independent from or dependent on environmental absorption efficiency, i.e., state-independent versus state-dependent restoration efforts. We determine (i) whether production or deforestation is the most detrimental from environmental and social welfare perspectives, and (ii) how state-dependent restoration process affects pollution accumulation and deforestation policies and the related environmental and social welfare consequences.

Friesl, Michal; Libich, Jan; Stehlík, Petr

doi: 10.1007/s10479-020-03626-4pmid: N/A

The global sports industry is extremely competitive. We focus on ice hockey and propose a (largely) costless reform to its operations that can potentially enhance the sport’s popularity by increasing the number of goals. The reform optimizes a logistic convention on the use of on-ice sides and off-ice benches, which affects the amount of attacking play and within-game scoring dynamics through the players’ substitutions. Using several empirical approaches, we provide estimates of the resulting scoring rise for all 11 geographically diverse competitions in our unique dataset. They are sizeable and robust to a number of checks, making case for trialling the reform in some (lower-tier) ice-hockey league.

Kabadurmus, Ozgur; Erdogan, Mehmet S.

doi: 10.1007/s10479-020-03654-0pmid: N/A

Emerging issues and new challenges of globalization have forced companies to design their supply chains for not only minimizing cost but also considering other factors. Supply chains are exposed to new environmental regulations to reduce their carbon emissions and compelled to consider other overlooked factors, such as risk. In this paper, we consider a multi-echelon multimodal supply chain network design problem with multiple products and components that take economic, environmental and risk factors into account. The problem is modeled as a Mixed Integer Linear Programming model and constrained by a carbon cap-and-trade scheme and a risk threshold. This novel problem realistically portrays the supply chain network design considering sustainability and reliability factors simultaneously. The proposed model has been tested on randomly generated hypothetical but realistic test instances. The impacts of different risk thresholds and unit carbon prices on the supply chain cost, risk and emissions are analyzed. The effects of multimodal transportation modes on cost, risk and emissions are also tested. Results prove that using multimodal transportation decreases supply chain cost and carbon emission. In addition, the total supply chain cost and carbon emission increase if the decision maker is risk-averse. The choice of transportation modes is sensitive only to emission levels.

Lozano, Sebastián; Soltani, Narges

doi: 10.1007/s10479-020-03662-0pmid: N/A

In this paper a new Data Envelopment Analysis (DEA) target setting approach is proposed based on a modification of the discrete Raiffa solution of bargaining problems. It is a multistage method that in the first step moves along the segment towards the ideal point, advancing along it as much as possible. If that first intermediate operating point is weak efficient (i.e. some input or output dimensions can be further improved) then the ideal point in the corresponding subspace is computed and a step towards it is taken and so forth until an efficient target is computed. Unlike the discrete Raiffa solution, the procedure is guaranteed to stop after a finite number of steps. The procedure is units and translation invariant and also provides an efficiency measure. The proposed approach can handle preference structure, non-discretionary variables and undesirable outputs.

Nguyen, Kien Trung; Hung, Nguyen Thanh

doi: 10.1007/s10479-020-03651-3pmid: N/A

We address the problem of modifying vertex weights of a block graph at minimum total cost so that a predetermined set of p connected vertices becomes a connected p-median on the perturbed block graph. This problem is the so-called inverse connected p-median problem on block graphs. We consider the problem on a block graph with uniform edge lengths under various cost functions, say rectilinear norm, Chebyshev norm, and bottleneck Hamming distance. To solve the problem, we first find an optimality criterion for a set that is a connected p-median. Based on this criterion, we can formulate the problem as a convex or quasiconvex univariate optimization problem. Finally, we develop combinatorial algorithms that solve the problems under the three cost functions in O(nlogn)\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$O(n\log n)$$\end{document} time, where n is the number of vertices in the underlying block graph.

Sun, Xinyu; Geng, Xin-Na; Liu, Tao

doi: 10.1007/s10479-020-03653-1pmid: N/A

In this paper, we consider due-window assignment scheduling in the proportionate flow shop setting with position-dependent weights where the weights depend on the position in which a job is scheduled. Under the common due-window (CONW) and slack due-window (SLKW) assignment methods, the location of the window and its properties are established. The objective is to determine the sequence of all jobs to minimize the total weighted cost function where the total weighted cost function must also consider the window start time and size. Based on these considerations, the corresponding algorithm and algorithm complexity are proposed.

Van Den Eeckhout, Mick; Maenhout, Broos; Vanhoucke, Mario

doi: 10.1007/s10479-020-03619-3pmid: N/A

In this paper, we study the project staffing problem with discrete time/resource trade-offs to minimise the personnel staffing budget. This staffing problem embeds activity scheduling flexibility by incorporating the project scheduling problem into the personnel staffing problem to improve the quality of the staffing plan. In addition, we introduce extra demand scheduling flexibility resulting from the design of alternative execution modes for the activities, modelled via discrete time/resource trade-offs. In this way, the project manager is able to decide on the team size and duration for every activity. We propose a two-stage methodology to first design specific alternative activity modes using heuristic rules-of-thumb and subsequently we assess the resulting quality, i.e. the staffing cost, via the integrated composition of the project schedule and associated staffing plan. The heuristic mode generation rules determine the selection of a limited set of relevant activities and modes. The computational results show that the impact of these heuristic generation rules on the staffing budget is dependent on the defined relation between different activity alternatives for a particular activity and on the estimated characteristics of the activity base modes. We show that by focusing on a particular well-chosen subset of activity alternatives or on a particular subset of activities, high-quality solutions realising most of the potential cost improvements resulting from the discrete time/resource trade-offs can be derived with a reduced effort.

Csató, László

doi: 10.1007/s10479-020-03637-1pmid: N/A

Fairness has several interpretations in sports, one of them being that the rules should guarantee incentive compatibility, namely, a team cannot be worse off due to better results in any feasible scenario. The current seeding regime of the most prestigious annual European club football tournament, the UEFA (Union of European Football Associations) Champions League, is shown to violate this requirement since the 2015/16 season. In particular, if the titleholder qualifies for the first pot by being a champion in a high-ranked league, its slot is given to a team from a lower-ranked association, which can harm a top club from the domestic championship of the titleholder. However, filling all vacancies through the national leagues excludes the presence of perverse incentives. UEFA is encouraged to introduce this policy from the 2021-24 cycle onwards.

Li, Daniel Li; Shan, Erfang

doi: 10.1007/s10479-020-03634-4pmid: N/A

We propose an efficient extension of the Myerson value for games with communication graph structure. Define a quotient game on set of the components of the graph, in which each component acts as a component-player. Then, each player in a component receives his payoff according to the Myerson value and an equal share of the surplus of the Shapley value obtained by the component in the quotient game. We show that this efficient extension of the Myerson value can be characterized by quotient component efficiency, fair distribution of surplus within component and coherence with the Myerson value for connected graphs.

Wiegand, Martin; Nadarajah, Saralees; Zhang, Yuanyuan

doi: 10.1007/s10479-020-03633-5pmid: N/A

In this note we introduce multivariate extensions to the bivariate discrete analogue to continuous probability distributions proposed in Barbiero [Annals of Operations Research, doi: 10.1007/s10479-019-03388-8, 2019]. We furthermore show that identical properties of the bivariate case also hold for n-variate discrete analogues.