The movement of empty trucks (dead-heading) incurs significant costs and creates greenhouse gas emissions and road congestion. A strategy to tackle the dead-heading problem is to identify long-term backhaul collaboration opportunities, in which shippers and carriers generate frequent movement patterns (lanes) from historical truck movements in stage one, and then use the identified lanes as inputs in stage two for an optimization problem to create load-sharing contracts that eliminate empty backhauls. Where existing research has treated these as separate stages, we present an end-to-end integrated decision-making framework to connect these two stages and show that an integrated system would improve performance across diverse measures through improved lane generation and optimization. Our research offers a new design framework for backhaul collaboration that integrates spatial analytics methods into an optimization model, with improvements in financial, environmental, and social benefits. We use fine-grained GPS telematics data collected from two large logistics companies and evaluate potential lanes using spatial analytics techniques. Our framework delivers up to 75% potential improvements compared to a standard approach commonly used in practice.

The assignment of personnel to teams is a fundamental managerial function typically involving several objectives and a variety of idiosyncratic practical constraints. Despite the prevalence of this task in practice, the process is seldom approached as an optimization problem over the reported preferences of all agents. This is due in part to the underlying computational complexity that occurs when intra‐team interpersonal interactions are taken into consideration, and also due to game‐theoretic considerations, when those taking part in the process are self‐interested agents. Variants of this fundamental decision problem arise in a number of settings, including, for example, human resources and project management, military platooning, ride sharing, data clustering, and in assigning students to group projects. In this article, we study an analytical approach to “team formation” focused on the interplay between two of the most common objectives considered in the related literature: economic efficiency (i.e., the maximization of social welfare) and game‐theoretic stability (e.g., finding a core solution when one exists). With a weighted objective across these two goals, the problem is modeled as a bi‐level binary optimization problem, and transformed into a single‐level, exponentially sized binary integer program. We then devise a branch‐cut‐and‐price algorithm and demonstrate its efficacy through an extensive set of simulations, with favorable comparisons to other algorithms from the literature.

In this article, we describe the decision support system that was developed for the assignment of courses to teaching modalities and rooms for the Fall semester of 2020 at the University of Connecticut (UConn). With the adoption of safety/mitigation standards imposed by the COVID-19 pandemic, the seating capacities of rooms were reduced by more than 70%, thus making virtually every existing room assignment for Fall 2020 infeasible. The demand for in-person instruction required the reassignment of a large number of courses to rooms, where not all requests for physical space could be accommodated. In order to maximize opportunities for in-person instruction, UConn introduced a teaching modality in which class meetings are attended on campus by only 50% of the enrolled students. As decision makers were given partial flexibility to assign teaching modalities to classes, the complexity of the assignment problem increased considerably, especially because the real-world instances involved hundreds of rooms and thousands of classes and required a quick solution turnaround in practice. In this article, we introduce this flexible assignment problem and describe the two mixed-integer programming formulations that were used to solve the real-world instances of the problem; in particular, one of the formulations leverages structural properties presented in this work in order to represent the problem in a more compact way. We explain how we tailored our algorithms to solve the real-world problem, describe the dynamics of the interactive decision support system created in this initiative, and present insights derived from our study.

We examined125 mass-stranding events of cetaceans (>=10 individuals) on New Zealand shores over the past 40 years. The wind, waves, wave refraction, shore slopes and tides at the dates and locations of these events were considered. The mass-strandings involved 10 different species, but by far the most common involved the Long-finned Pilot Whale, Globicephala melas. Our hypothesis is that mass-stranding is a three-stage process. The first stage is when an animal becomes ill, its body may become bloated and float on the surface, and the wind and waves may drive it ashore. We assume the second stage is that the dying or dead body may be accompanied by pod members as a result of strong social bonds. The third stage involves the tides and the beach slope. If these are of sufficient amplitude, the nearby attendees will quickly become stranded in the intertidal of a gently sloping beach as the water level falls. We have evaluated evidence for the first and third stages. In the overwhelming majority (91%) of the mass-strandings (omitting events inside estuaries), the available data showed that wind and waves would drive floating objects (bodies) toward the stranding site. Examination of the nearshore slopes and the tide ranges showed that the vast majority of the stranding sites were slowly shelving beaches where the tides would retreat rapidly over 10s of metres. These 2 results are even more pronounced if only Pilot Whale mass strandings are considered.

We develop a potentially widely applicable framework for analysing the vulnerability, resilience risk and exposure of chondrichthyan species to all types of anthropogenic stressors in the marine environment. The approach combines the three components of widely applied vulnerability analysis (exposure, sensitivity and adaptability) (ESA) with three components (exposure, susceptibility and productivity) (ESP) of our adaptation of productivity– susceptibility analysis (PSA). We apply our 12- step ESA‒ ESP analysis to evaluate the vulnerability (risk of a marked reduction of the population) of each of 132 chondrichthyan species in the Exclusive Economic Zone of southern Australia. The vulnerability relates to a species’ resilience to a spatial (or suitability) reduction of its habitats from exposure to up to eight climate change stressors. Vulnerability also relates to anthropogenic mortality added to natural mortality from exposure to the stressors of five types of fishing and seven other types of anthropogenic hazards. We use biological attributes as risk factors to evaluate risk related to resilience at the species or higher taxonomic level. We evaluate each species’ exposure to anthropogenic stressors by assigning it to one of six ecological groups based on its lifestyle (demersal versus pelagic) and habitat, defined by bathymetric range and substrates. We evaluate vulnerability for 11 scenarios: 2000– 2006 when fishing effort peaked; 2018 following a decade of fisheries management reforms; low, medium and high standard future carbon dioxide equivalent emissions scenarios; and their six possible climate– fishing combinations. Our results demonstrate the value of refugia from fishing and how climate change exacerbates the risks from fishing.

Much of the prominent literature describing behavior in eBay-like marketplaces emphasizes the successful use of "sniping" agents that wait until the last moments of an auction to bid (truthfully) on behalf of a human user. These agents fare well against "naive" agents (typically assumed to be those who bid incrementally on the most profitable open auction) who do not get the chance to respond to the snipe-bid placed in the final seconds. This reasoning, however, tends to ignore the effect of the poor coordination that occurs as more and more players attempt the sniping agent strategy, thereby raising prices above their minimum possible competitive equilibrium levels. Using proprietary data purchased from eBay, encompassing all bids submitted on four specific product types over a 3-month period, we analyze the allocative efficiency, price, and bidder surplus using a software agent and compare this to the historical performance. After showing a significant amount of "money left on the table" in the historical record, we proceed to demonstrate how bidders can significantly improve their surplus (i.e., observed profit) by adopting a "seek-and-protect" agent. If bidders go further and implement sequential-auction shading strategies, they can incrementally improve their surplus, but sometimes at the expense of allocative efficiency. Acknowledging that each bidder's time window of interest is inherently unobservable, we vary the length of bidders' consumption windows and find similar results.

In recent years, several universities have adopted an algorithmic approach to the allocation of seats in courses, for which students place bids (typically by ordering or scoring desirable courses), and then seats are awarded according to a predetermined procedure or mechanism. Designing the appropriate mechanism for translating bids into student schedules has received attention in the literature, but there is currently no consensus on the best mechanism in practice. In this paper, we introduce five new algorithms for this course-allocation problem, using various combinations of matching algorithms, second-price concepts, and optimization, and compare our new methods with the natural benchmarks from the literature: the (proxy) draft mechanism and the (greedy) bidding-point mechanism. Using simulation, we compare the algorithms on metrics of fairness, efficiency, and incentive compatibility, measuring their ability to encourage truth telling among boundedly rational agents. We find good results for all of our methods and that a two-stage, full-market optimization performs best in measures of fairness and efficiency but with slightly worse incentives to act strategically compared with the best of the mechanisms. We also find generally negative results for the bidding-point mechanism, which performs poorly in all categories. These results can help guide the decision of selecting a mechanism for course allocation or for similar assignment problems, such as project team assignments or sports drafts, for example, in which efficiency and fairness are of utmost importance but incentives must also be considered. Additional robustness checks and comparisons are provided in the online supplement.

We report results from the first detailed investigation of elasmobranch bycatch that contains data on species, sex, and length-frequency distributions of animals collected in the coastal south-eastern and entrance region of the Gulf of California. Using data from fishery-independent prawn trawl surveys between 2011-17, we found differences between years and zones in the number of species per tow in summer when more samples were taken, but we did not find differences in autumn and winter. We present size-frequency distributions with size at first maturity for Urobatis halleri, Urotrygon chilensis, Rhinoptera steindachneri, Hypanus dipterurus, Gymnura marmorata, and Pseudobatos glaucostigmus, which were the species most frequently present in the prawn trawls during the surveys. These distributions are presented by zone, depth stratum, and season (mainly summer, when commercial prawn trawling is prohibited, and thus information from commercial catches is not available). We found significant differences in the mean size between mature females and mature males for five of these six species. We also found that fish escape devices installed in the prawn nets early in 2016 improved the escape of mid-sized rays, demonstrating size selectivity of the fishery and suggesting the potential to improve further the escape of large-sized rays by modifying fish escape devices. Furthermore, the large number of rays caught (21 species) compared with the number of sharks caught (four species) suggests much lower catchabilities for sharks than for rays in demersal prawn trawl gear.

We study the planning and scheduling of order shipments among laboratories of an instrument‐calibration company. To address a generic version of the company’s combined routing and scheduling problem, we introduce a model variant with simultaneous pickups and deliveries in which consistency of site visits is also desired. We provide alternative formulations of the problem and propose branch‐and‐check and branch‐and‐price implementations, with an analysis of the instance characteristics for which each of these algorithms outperforms the other. Using the data collected from the company, our results indicate that the proposed framework can help the company to significantly reduce transportation costs and shipment times. We also investigate the influence of consistency and tardiness bounds on transportation costs, showing that while tardiness bounds significantly increase transportation costs, the enforcement of consistency requirements results in more consistent solutions at only slightly higher cost. The impact of enforcing consistency requirements increases when tighter tardiness bounds are imposed.

Paired basic amino acid cleaving enzyme 4 (PACE4), a serine endoprotease of the proprotein convertases family, has been recognized as a promising target for prostate cancer. We previously reported a selective and potent peptide-based inhibitor for PACE4, named the multi-Leu peptide (Ac-LLLLRVKR-NH2 sequence), which was then modified into a more potent and stable compound named C23 with the following structure: Ac-dLeu-LLLRVK-Amba (Amba: 4-amidinobenzylamide). Despite improvements in both in vitro and in vivo profiles of C23, its selectivity for PACE4 over furin was significantly reduced. We examined other Arg-mimetics instead of Amba to regain the lost selectivity. Our results indicated that the replacement of Amba with 5-(aminomethyl)picolinimidamide increased affinity for PACE4 and restored selectivity. Our results also provide a better insight on how structural differences between S1 pockets of PACE4 and furin could be employed in the rational design of selective inhibitors.

The assignment of personnel to teams is a fundamental and ubiquitous managerial function, typically involving several objectives and a variety of idiosyncratic practical constraints. Despite the prevalence of this task in practice, the process is seldom approached as a precise optimization problem over the reported preferences of all agents. This is due in part to the underlying computational complexity that occurs when quadratic (i.e., intra-team interpersonal) interactions are taken into consideration, and also due to game-theoretic considerations, when those taking part in the process are self-interested agents. Variants of this fundamental decision problem arise in a number of settings, including, for example, human resources and project management, military platooning, sports-league management, ride sharing, data clustering, and in assigning students to group projects. In this paper, we study a mathematical-programming approach to team formation focused on the interplay between two of the most common objectives considered in the related literature: economic efficiency (i.e., the maximization of social welfare) and game-theoretic stability (e.g., finding a core solution when one exists). With a weighted objective across these two goals, the problem is modeled as a bi-level binary optimization problem, and transformed into a single-level, exponentially sized binary integer program. We then devise a branch-cut-and-price algorithms and demonstrate its efficacy through an extensive set of simulations, with favorable comparisons to other algorithms from the literature.

Experimental tests of expected-utility theory EU have accumulated empirical observations in which the predictions of EU are systematically violated. The cumulative prospect theory CPT explains violations such as the Allais paradoxes and fourfold pattern of risk attitudes as resulting from nonlinear probability transformations. Here we show that the classical paradoxes for decisions under risk can be explained with preferences that are linear in probabilities for any choice set and that maximize an expected-utility function with respect to an endogenous target return. We introduce the maximin payoff as a plausible and even natural target return from a choice set and show that the resulting target-adjusted utility TAU model explains additional empirical observations such as the scale dependence of the Allais paradox that cannot be explained by standard specifications of CPT. Further, using data from three prominent laboratory experiments, we find that TAU is effective in explaining observed behaviors.This paper was accepted by James Smith, decision analysis.

Combinatorial auctions represent one of the most prominent areas of research in the intersection of Operations Research (OR) and Economics. First proposed for practical governmental applications by Rassenti et al. (1982), a combinatorial auction (CA) is an auction for many items in which bidders submit bids on combinations of items, or packages. CAs also are referred to as “package auctions” or auctions with “package bidding.” In a general CA, a bidder may submit bids on any arbitrary collection of packages. The “winner-determination problem” identifies the value maximizing assignment given the package bids. This problem is as complex as the Weighted Set-Packing problem, and hence NP-hard (see Rothkopf et al. 1998).

This paper describes a carbon trading game to be played in a classroom setting. The game is modeled on real-world electric power markets with a carbon dioxide (CO 2 ) emissions cap, often referred to as a “cap-and-trade” system. Players assume the roles of competing utilities, each with a fossil fuel plant and a renewable energy plant. Any electricity generated by fossil fuel requires offsetting carbon credits, which are available via auction. Depending on the auction price, it can be cheaper or more expensive to generate electricity with fossil fuel versus renewables. The goals of the game are: for students to become acquainted with cap-and-trade markets; to understand how regulatory policy applied to a market can induce environmental benefits; to discover how to mathematically derive strategies; to get a taste of basic game theory, auctions, and the newsvendor problem; and to meet these objectives in a fun setting. While fairly straightforward and simplified to provide symmetry among student competitors, the game can lead to surprisingly interesting results. This paper describes the game and how to facilitate it, presents strategies, analyzes games that were played, introduces novel quantitative measures to evaluate the quality of game play, and offers a number of suggestions for extending the game. The online appendices are available at https://doi.org/10.1287/ited.2017.0171 . The teaching note is available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .

Estimating contemporary genetic structure and population connectivity in marine species is challenging, often compromised by genetic markers that lack adequate sensitivity, and unstructured sampling regimes. We show how these limitations can be overcome via the integration of modern genotyping methods and sampling designs guided by LiDAR and SONAR data sets. Here we explore patterns of gene flow and local genetic structure in a commercially harvested abalone species (Haliotis rubra) from southeastern Australia, where the viability of fishing stocks is believed to be dictated by recruitment from local sources. Using a panel of microsatellite and genomewide SNP markers, we compare allele frequencies across a replicated hierarchical sampling area guided by bathymetric LiDAR imagery. Results indicate high levels of gene flow and no significant genetic structure within or between benthic reef habitats across 1400 km of coastline. These findings differ to those reported for other regions of the fishery indicating that larval supply is likely to be spatially variable, with implications for management and long-term recovery from stock depletion. The study highlights the utility of suitably designed genetic markers and spatially informed sampling strategies for gaining insights into recruitment patterns in benthic marine species, assisting in conservation planning and sustainable management of fisheries.

The effect of a short-term feeding and starvation experiment on juvenile abalone (Haliotis rubra × H. laevigata) was investigated (average length = 67 mm; average weight = 48 g). All aquaculture experiments were conducted at The University of Melbourne, Australia. Artificial feed was supplied ad libitum to the fed group, and no feed was supplied to the starved group. A modified metabolite extraction protocol using deuterated solvents was developed for 1H-NMR-based metabolite profiling of digestive gland in response to the short-term feeding/starvation experiment, to avoid lyophilisation prior to biochemical analysis. PLS-DA revealed that fed and starved abalone are metabolically distinct from each other after 28 and 56 days. After 28 days, the fed group was defined by an increase in arginine, glucose, glutamate, glycine, inosine and uracil (P < 0.05), and the starved group was defined by an increase in N,N-dimethylglycine. After 56 days, the fed group still displayed increased glucose (P < 0.05), while N,N-dimethylglycine remained elevated in the starved group (P < 0.05). Arginine and glycogen were all higher at 28 days compared to 56 days, suggesting decreased anaerobic energy production at the later time point. Only glucose and N,N-dimethylglycine were significantly different between the fed and starved groups after 56 days, suggesting that abalone had not acclimatised to the starvation treatment after 28 days. These results infer N,N-dimethylglycine is a robust marker for short-term starvation in abalone. 1H-NMR was also conducted on the artificial feed and starved abalone faecal matter, revealing the biochemical differences between them and digestive gland tissue. These methodology and results will facilitate a deeper understanding of the nutritional and physiological requirements of abalone in an aquaculture setting.

The inside cover picture shows a challenging ′journey′ from a lead PACE4 inhibitor (ML peptide) into a drug-like compound for in vivo administration. Different routes have been taken to improve properties of the ML inhibitor, including N-terminal PEGylation and lipidation. The effect of these modifications on activity, stability, toxicity, and cell penetration of the resulting analogs was evaluated. Our results show that the best inhibitor was obtained not by N-terminal extensions but the protection of both ends with a d-amino acid residue and an arginine mimetic, indicating that simple solutions are sometimes more effective. These modifications significantly improved activity and stability profile and led to a compound ready for in vivo studies as a potential anti-prostate cancer agent. More information can be found in the Full Paper by Yves L. Dory, Robert Day et al. on page 289 in Issue 3, 2016 (DOI: 10.1002/cmdc.201500532).

We introduce an auction design framework for large markets with hundreds of items and complex bidder preferences. Such markets typically lead to computationally hard allocation problems. Our new framework consists of compact bid languages for sealed-bid auctions and methods to compute second-price rules such as the Vickrey–Clarke–Groves or bidder-optimal, core-selecting payment rules when the optimality of the allocation problem cannot be guaranteed. To demonstrate the efficacy of the approach for a specific, complex market, we introduce a compact bidding language for TV advertising markets and investigate the resulting winner-determination problem and the computation of core payments. For realistic instances of the respective winner-determination problems, very good solutions with a small integrality gap can be found quickly, although closing the integrality gap to find marginally better solutions or prove optimality can take a prohibitively large amount of time. Our subsequent adaptation of a constraint-generation technique for the computation of bidder-optimal core payments to this environment is a practically viable paradigm by which core-selecting auction designs can be applied to large markets with potentially hundreds of items. Such auction designs allow bidders to express their preferences with a low number of parameters, while at the same time providing incentives for truthful bidding. We complement our computational experiments in the context of TV advertising markets with additional results for volume discount auctions in procurement to illustrate the applicability of the approach in different types of large markets. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.2076 . This paper was accepted by Lorin Hitt, information systems.

Ecosystem-based management of marine fisheries requires the use of simulation modelling to investigate the system-level impact of candidate fisheries management strategies. However, testing of fundamental assumptions such as system structure or process formulations is rarely done. In this study, we compare the output of three different ecosystem models (Atlantis, Ecopath with Ecosim, and OSMOSE) applied to the same ecosystem (the southern Benguela), to explore which ecosystem effects of fishing are most sensitive to model uncertainty. We subjected the models to two contrasting fishing pressure scenarios, applying high fishing pressure to either small pelagic fish or to adult hake. We compared the resulting model behaviour at a system level, and also at the level of model groups. We analysed the outputs in terms of various commonly used ecosystem indicators, and found some similarities in the overall behaviour of the models, despite major differences in model formulation and assumptions. Direction of change in system-level indicators was consistent for all models under the hake pressure scenario, although discrepancies emerged under the small-pelagic-fish scenario. Studying biomass response of individual model groups was key to understanding more integrated system-level metrics. All three models are based on existing knowledge of the system, and the convergence of model results increases confidence in the robustness of the model outputs. Points of divergence in the model results suggest important areas of future study. The use of feeding guilds to provide indicators for fish species at an aggregated level was explored, and proved to be an interesting alternative to aggregation by trophic level.