Simple assembly line balancing problem under task deterioration

This paper introduces the effect of task deterioration in simple assembly line balancing problem. In many realistic assembly lines, a deterioration task is considered when a task is started earlier than the assigned time since the station time is constant and the earliness of the task does not reduce the cycle time. This phenomenon is known as deteriorating tasks. Therefore, we seek an optimal assignment and schedule of tasks in workstations, in order to minimize the number of stations for a given cycle time, which is known as SALBP-1. For this purpose, a mathematical model is proposed. Since the pure SALBP-1 is proved to be NP-hard and considering task deterioration complicates problem further, we propose a genetic algorithm for solving such problem. Several well-known test problems are solved to study the performance of the proposed approach

Transforming climate science into usable services: The effectiveness of co-production in promoting uptake of climate information by smallholder farmers in Senegal

Does the provision of weather and climate information services (WCIS) enhance farmer’s use of forecasts in informing farm decisions? This paper assesses the effectiveness of the Multi-disciplinary Working Group (MWG) – a WCIS co-production initiative in Senegal in influencing farmers uptake of weather and climate information (WCI). WCIS are increasingly gaining importance and widely touted as critical in helping farmers adapt to climate variability. While there have been various WCIS initiatives producing and translating climate data into tailored information and knowledge in different parts of the world, there is hardly any rigorous evidence assessing their effectiveness in improving uptake. In this assessment, we use innovative survey methods and apply rigorous analytical approaches that control for self-selection bias to establish causal linkages between the MWG and use of WCIS. Our findings indicate that MWGs are positively associated with farmers’ awareness, access and uptake of WCI resulting in farm management responses depending on the type of information used. The presence of MWGs generally increases farmer’s awareness of WCI by 18%, access by 12% and uptake by 10%. Furthermore, use of seasonal forecasts is generally associated with a higher proportion of farmers using improved seed, fertilizers and manure, but negatively with crop diversification within MWG locations. This suggests that participatory approaches in the provision of tailored climate information and advisory services can lead to higher uptake and use among farmers in informing farm management responses for better adaptation to climate change. We highlight lessons for improved evaluations of WCIS in future

Natural history of SLC11 genes in vertebrates: tales from the fish world

<p>Abstract</p> <p>Background</p> <p>The <it>SLC11A1/Nramp1 </it>and <it>SLC11A2/Nramp2 </it>genes belong to the <it>SLC11/Nramp </it>family of transmembrane divalent metal transporters, with <it>SLC11A1 </it>being associated with resistance to pathogens and <it>SLC11A2 </it>involved in intestinal iron uptake and transferrin-bound iron transport. Both members of the <it>SLC11 </it>gene family have been clearly identified in tetrapods; however <it>SLC11A1 </it>has never been documented in teleost fish and is believed to have been lost in this lineage during early vertebrate evolution. In the present work we characterized the <it>SLC11 </it>genes in teleosts and evaluated if the roles attributed to mammalian <it>SLC11 </it>genes are assured by other fish specific <it>SLC11 </it>gene members.</p> <p>Results</p> <p>Two different <it>SLC11 </it>genes were isolated in the European sea bass (<it>Dicentrarchus. labrax</it>), and named <it>slc11a2-α </it>and <it>slc11a2-β</it>, since both were found to be evolutionary closer to tetrapods <it>SLC11A2</it>, through phylogenetic analysis and comparative genomics. Induction of <it>slc11a2-α </it>and <it>slc11a2-β </it>in sea bass, upon iron modulation or exposure to <it>Photobacterium damselae </it>spp. <it>piscicida</it>, was evaluated in <it>in vivo </it>or <it>in vitro </it>experimental models. Overall, <it>slc11a2-α </it>was found to respond only to iron deficiency in the intestine, whereas <it>slc11a2-β </it>was found to respond to iron overload and bacterial infection in several tissues and also in the leukocytes.</p> <p>Conclusions</p> <p>Our data suggests that despite the absence of <it>slc11a1</it>, its functions have been undertaken by one of the <it>slc11a2 </it>duplicated paralogs in teleost fish in a case of synfunctionalization, being involved in both iron metabolism and response to bacterial infection. This study provides, to our knowledge, the first example of this type of sub-functionalization in iron metabolism genes, illustrating how conserving the various functions of the SLC11 gene family is of crucial evolutionary importance.</p

Competition of two supply chains with different risk structures: applying market research option

Demand uncertainty obliges all participants through a supply chain to make decisions under uncertainty. These decisions extend across price, investment, production, and inventory quantities. We take account of competition between two supply chains under demand uncertainty. These chains internally are involved in vertical pricing competition; however, they externally participate in horizontal pricing and service level competitions by offering a single-type product to the market. Since firms may have various attitudes against demand uncertainty and its related risks, different risk structures for competitive supply chains are considered. We assume that risk-averse firms are able to decrease demand uncertainty by information gathered from market research. For risk-averse participants in a chain, market research investment is an appropriate ground for vertical coordination, which diminishes risk through a supply chain. Optimal strategies based on game theory are obtained for different risk structures; furthermore, for each structure the effects of risk sensitivity as well as market research efficiency on these optimal strategies are investigated. Finally, we propose two scenarios for information sharing between risk-averse participants

Supply Chains Competition under Uncertainty Concerning Player’s Strategies and Customer Choice Behavior: A Generalized Nash Game Approach

Decision makers in a supply chain confront two main sources of uncertainty in market environment including uncertainty about customers purchasing behaviors and rival chains strategies. Focusing on competition between two supply chains, it is considered that each customer as an independent player selects products of these chains based on random utility model. Similar to quantal response equilibrium approach, we take account of customer rationality as an exogenous parameter. Moreover, it is assumed that decision makers in a supply chain can perceive an estimation of rival strategies about price and service level formulated in the model by fuzzy strategies. In the competition model, chain’s decision makers consider a subjective probability for wining each customer which is formulated by coupled constraints. These constraints connect chains strategies regarding to each customer and yield a generalized Nash equilibrium problem. Since price cutting and increasing service level are main responses to rival supply chain, after calculating optimal strategies, we show that more efficient responses depend on customer preferences

Ideal and anti-Ideal decision making units: A fuzzy DEA approach

In this paper, by introducing two virtual decision-making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) with fuzzy inputs-outputs, the efficiency evaluation of DMUs are done by fuzzy data envelopment analysis (FDEA). Therefore, we evaluate DMUs from the perspective of the best and worst possible relative efficiency. For each DMU two efficiencies are calculated while inputs and outputs are fuzzy. These two distinctive efficiencies are combined with the closeness coefficient (CC) index. The CC index is then used for an overall ranking of all DMUs. Finally, we compare the result of proposed fuzzy DEA model with León et al.’s (2003) results by representing a numerical example

An Application of Fuzzy Numbers Ranking in Performance Analysis

Data Envelopment Analysis (DEA) is a mathematical optimization technique that measures the relative efficiency of Decision Making Units (DMUs) with multiple input-output. In traditional DEA models, the data of different DMUs are assumed to be measured by precise values. But, in many real applications there are some imprecise data which represented by fuzzy numbers. In this study, an application of ranking fuzzy numbers is introduced and CCR model with fuzzy inputs and outputs in DEA is extended to propose an innovative version of fuzzy DEA (FDEA). In fact, we transform a fuzzy DEA model to a conventional crisp model by applying ranking fuzzy numbers method. Three numerical examples including an application to bank branches assessment at capital city of Iran are finally applied using the proposed fuzzy CCR model to show its applications and the differences from the other fuzzy DEA models