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Abstract:
According to Brooks' law for software development projects "adding manpower to a late software project makes it later." Building on Brooks' law, we argue that complexity increases the maximum team size in software development projects (Hypothesis 1), and that maximum team size decreases software development productivity (Hypothesis 2). We test these hypotheses with a dataset of 117 software development projects conducted in Finland. Hypothesis 1 is supported for two out of three measures of complexity. We also find strong support for Hypothesis 2. In order to mitigate the negative impact of team size on productivity, managers should pay close attention to the logical complexity of software as well as the interfaces to other software.

Project Management, Software Development, Software Productivity, Complexity, Project Team Size

Abstract:
The condition of the used products acquired by remanufacturers is often highly variable. Acquisition and sorting policies can be used to manage the complexity that used product condition adds to remanufacturing operations. This paper examines the acquisition and sorting decisions faced by a remanufacturer. We analyze scenarios in which condition is dichotomous, as well as more complex condition distributions. For each distribution type, we present simple deterministic yield models for optimizing the acquisition and sorting decisions. We then present more complex (but typically more realistic) stochastic yield models of these problems. By comparing the solutions to the models in numerical studies, we are able to observe the benefits of incorporating yield uncertainty into these decisions. We find that the simplifying assumption of deterministic yield is often reasonable, as it results in near-optimal solutions. For situations in which exact stochastic yield solutions are desired, we present approaches for finding the optimal solution to the stochastic yield problem.

remanufacturing, reverse supply chain, stochastic yield