Multiprocessor task scheduling in multistage hyrid flowshops: a genetic algorithm approach

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, that is, the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process industries. A genetic algorithm (GA) is developed to solve the problem. The GA is tested against a lower bound from the literature as well as against heuristic rules on a test bed comprising 400 problems with up to 100 jobs, 10 stages, and with up to five processors on each stage. For small problems, solutions found by the GA are compared to optimal solutions, which are obtained by total enumeration. For larger problems, optimum solutions are estimated by a statistical prediction technique. Computational results show that the GA is both effective and efficient for the current problem. Test problems are provided in a web site at www.benchmark.ibu.edu.tr/mpt-h; fsp

Tailoring hyper-heuristics to specific instances of a scheduling problem using affinity and competence functions

Hyper-heuristics are high level heuristics which coordinate lower level ones to solve a given problem. Low level heuristics, however, are not all as competent/good as each other at solving the given problem and some do not work together as well as others. Hence the idea of measuring how good they are (competence) at solving the problem and how well they work together (their affinity). Models of the affinity and competence properties are suggested and evaluated using previous information on the performance of the simple low level heuristics. The resulting model values are used to improve the performance of the hyper-heuristic by tailoring it not only to the specific problem but the specific instance being solved. The test case is a hard combinatorial problem, namely the Hybrid Flow Shop scheduling problem. Numerical results on randomly generated as well as real-world instances are included

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Sales force optimization to efficiently supply small stores in emerging markets

Supplying High Frequency Stores (HFS) is challenging and appealing topic for fast-moving consumers goods (FMCG) companies that are looking for growth in emerging markets. The distribution footprint in those markets consists of a range family-owned nanostores that play a key role in the retail landscape. FMCG companies still need people to sell products and drive revenue while optimizing sales force. The present paper attempts to provide a model for an effective strategy to cover and to supply nanostores. The problem of concern is modeled as an assignment problem, combined with side constraints regarding disruption of pre-assignments and profit potential balance. © ILS 2018 - Information Systems, Logistics and Supply Chain, Proceedings. All rights reserved

Ab initio calculations of electronic band structure and charge densities of zinc blende-type GaN, BN and their solid solution B0.5Ga0.5N

First principles calculations of the electronic band structures of zinc blende-type GaN and BN and their 1 : 1 mixture B0.5Ga0.5N were carried out within DFT using the augmented plane wave method with both GGA and LDA approximations for the effects of exchange and correlation. Equilibrium lattice constants were determined from the total-energy minimization method. The results are compared with those of previous calculations and with experimental measurements. In agreement with these data, ZB-BN is an indirect (Γ →X) wide-gap semiconductor (4.35 eV) while ZB-GaN has a direct gap of 1.9 eV atΓ . For ZBB0.5Ga0.5N we predict a direct band gap of 3.35 eV. Electron charge densities are computed for the unit cell, and ionicity factors are derived for all systems