Twin-crane scheduling during seaside workload peaks with a dedicated handshake area

To enable the efficient division of labor in container yards, many large ports apply twin cranes, two identical automated stacking cranes each dedicated to one of the transfer zones on the seaside and landside. The use of a handshake area, a bay of containers that separates the dedicated areas of the two cranes, is a simple means to avoid crane interference. Inbound containers arriving in the transfer zone of one crane and dedicated to a stacking position of the other crane’s area are placed intermediately in the handshake area by the first crane and then taken over by the second crane, and vice versa for outbound containers. Existing research only evaluates simple heuristics and rule-based approaches for the coordination of twin cranes interconnected by a handshake area. For this setting, accounting for precedence constraints due to stacking containers in the handshake area, we derive exact solution procedures under a makespan minimization objective. In this way, a comprehensive computational evaluation is enabled, which benchmarks heuristics with optimal solutions and additionally compares alternative crane settings (i.e., without workload sharing and cooperation with flexible handover). We further provide insights into where to position the handshake area. Our results reveal that when planning is too simple (i.e., with a rule-based approach), optimality gaps become large, but with sophisticated optimization, the price of a simplified crane coordination via a handshake area is low.

The effects of reputation on inequality in network cooperation games

In the last several decades, ample evidence from across evolutionary biology, behavioural economics and econophysics has solidified our knowledge that reputation can promote cooperation across different contexts and environments. Higher levels of cooperation entail higher final payoffs on average, but how are these payoffs distributed among individuals? This study investigates how public and objective reputational information affects payoff inequality in repeated social dilemma interactions in large groups. I consider two aspects of inequality: excessive dispersion of final payoffs and diminished correspondence between final payoff and cooperative behaviour. I use a simple heuristics-based agent model to demonstrate that reputational information does not always increase the dispersion of final payoffs in strategically updated networks, and actually decreases it in randomly rewired networks. More importantly, reputational information almost always improves the correspondence between final payoffs and cooperative behaviour. I analyse empirical data from nine experiments of the repeated Trust, Helping, Prisoner's Dilemma and Public Good games in networks of ten or more individuals to provide partial support for the predictions. Our research suggests that reputational information not only improves cooperation but may also reduce inequality. This article is part of the theme issue ‘The language of cooperation: reputation and honest signalling'.

Rules of thumb and cultural evolution: How simple heuristics have guided human adaptation and the emergence of cultural complexity

This article combines insights from ecological rationality and cultural evolution to illustrate how simple heuristics – colloquially, “rules of thumb” – have guided human behaviour and the evolution of complex cultures. Through a variety of examples and case studies, we discuss how human cultures have used rules of thumb in domains as diverse as foraging, resource management, social learning, moral judgment, and cultural niche construction. We propose four main arguments. Firstly, we argue that human societies have a rich cultural history in applying rules of thumb to guide daily activities and social organization. Second, we emphasise how rules of thumb may be convenient units of cultural transmission and high-fidelity social learning – the backbones of cumulative cultural evolution. Third, we highlight how rules of thumb can facilitate efficient decision making by making use of environmental and bodily features. Fourth, we discuss how simple rules of thumb may serve as building blocks for the emergence of more complex cultural patterns. This paper sets a research agenda for studying how simple rules contribute to cultural evolution in the past, the present, and the Anthropocene future.

Global Optimisation through Hyper-Heuristics: Unfolding Population-Based Metaheuristics

Optimisation has been with us since before the first humans opened their eyes to natural phenomena that inspire technological progress. Nowadays, it is quite hard to find a solver from the overpopulation of metaheuristics that properly deals with a given problem. This is even considered an additional problem. In this work, we propose a heuristic-based solver model for continuous optimisation problems by extending the existing concepts present in the literature. We name such solvers ‘unfolded’ metaheuristics (uMHs) since they comprise a heterogeneous sequence of simple heuristics obtained from delegating the control operator in the standard metaheuristic scheme to a high-level strategy. Therefore, we tackle the Metaheuristic Composition Optimisation Problem by tailoring a particular uMH that deals with a specific application. We prove the feasibility of this model via a two-fold experiment employing several continuous optimisation problems and a collection of diverse population-based operators with fixed dimensions from ten well-known metaheuristics in the literature. As a high-level strategy, we utilised a hyper-heuristic based on Simulated Annealing. Results demonstrate that our proposed approach represents a very reliable alternative with a low computational cost for tackling continuous optimisation problems with a tailored metaheuristic using a set of agents. We also study the implication of several parameters involved in the uMH model and their influence over the solver performance.

The Journey from Episode to Evaluation: How Travelers Arrive at Summary Evaluations

Understanding how travelers evaluate their overall trip experience is important to travel research. Psychologists suggested that these retrospective evaluations are often made by temporally integrating multiple episodes following simple heuristics that draw on key episodes only, typically the peak and end episodes, rather than considering every episodic evaluation, weighted by its respective duration. To test these aggregation rules, a survey adapting the Day Reconstruction Method was conducted in 2017 among 691 travelers to Macau. Our findings reveal that summary evaluations are better predicted using an arithmetic average of all episodic evaluations, instead of the peak-end rule. This may be explained by the lengthier and more complex nature of travel, compared with other extended experiences that psychologists have investigated. The immediate theoretical implications are that (1) aggregate trip evaluations are influenced by most episodes, and (2) the relative duration of individual episodes is disregarded. Theoretical, methodological, and practical implications are discussed.