Bi-criterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic

An assembly supply chain (SC) is composed of stages that provide the components, assemble both sub-assemblies and final products, and deliver products to the customer. The activities carried out in each stage could be performed by one or more options, thus the decision-maker must select the set of options that minimises the cost of goods sold (CoGS) and the lead time (LT), simultaneously. In this paper, an ant colony-based algorithm is proposed to generate a set of SC configurations using the concept of Pareto optimality. The pheromones are updated using an equation that is a function of the CoGS and LT. The algorithm is tested using a notebook SC problem, widely used in literature. The results show that the ratio between the size of the Pareto Front computed by the proposed algorithm and the size of the one computed by exhaustive enumeration is 90%. Other metrics regarding error ratio and generational distance are provided as well as the CPU time to measure the performance of the proposed algorithm.This work was partially supported by the Spanish Ministerio de Ciencia e Innovación, under the project “Gestión de movilidad eficiente y sostenible, MOVES” with grant reference TIN2011-28336

Compromising between European and US allergen immunotherapy schools: Discussions from GUIMIT, the Mexican immunotherapy guidelines

Background: Allergen immunotherapy (AIT) has a longstanding history and still remains the only disease-changing treatment for allergic rhinitis and asthma. Over the years 2 different schools have developed their strategies: the United States (US) and the European. Allergen extracts available in these regions are adapted to local practice. In other parts of the world, extracts from both regions and local ones are commercialized, as in Mexico. Here, local experts developed a national AIT guideline (GUIMIT 2019) searching for compromises between both schools. Methods: Using ADAPTE methodology for transculturizing guidelines and AGREE-II for evaluating guideline quality, GUIMIT selected 3 high-quality Main Reference Guidelines (MRGs): the European Academy of Allergy, Asthma and Immunology (EAACI) guideines, the S2k guideline of various German-speaking medical societies (2014), and the US Practice Parameters on Allergen Immunotherapy 2011. We formulated clinical questions and based responses on the fused evidence available in the MRGs, combined with local possibilities, patient's preference, and costs. We came across several issues on which the MRGs disagreed. These are presented here along with arguments of GUIMIT members to resolve them. GUIMIT (for a complete English version, see Supplementary data) concluded the following: Results: Related to the diagnosis of IgE-mediated respiratory allergy, apart from skin prick testing complementary tests (challenges, in vitro testing and molecular such as species-specific allergens) might be useful in selected cases to inform AIT composition. AIT is indicated in allergic rhinitis and suggested in allergic asthma (once controlled) and IgE-mediated atopic dermatitis. Concerning the correct subcutaneous AIT dose for compounding vials according to the US school: dosing tables and formula are given; up to 4 non-related allergens can be mixed, refraining from mixing high with low protease extracts. When using European extracts: the manufacturer's indications should be followed; in multi-allergic patients 2 simultaneous injections can be given (100% consensus); mixing is discouraged. In Mexico only allergoid tablets are available; based on doses used in all sublingual immunotherapy (SLIT) publications referenced in MRGs, GUIMIT suggests a probable effective dose related to subcutaneous immunotherapy (SCIT) might be: 50–200% of the monthly SCIT dose given daily, maximum mixing 4 allergens. Also, a table with practical suggestions on non-evidence-existing issues, developed with a simplified Delphi method, is added. Finally, dissemination and implementation of guidelines is briefly discussed, explaining how we used online tools for this in Mexico. Conclusions: Countries where European and American AIT extracts are available should adjust AIT according to which school is followed

Managing inventory levels and time to market in assembly supply chains by swarm intelligence algorithms

The proposed work addresses the problem of placing safety stock under the guaranteed-service model when a set of supplying, manufacturing and delivery stages model the production system. Every stage has a set of options that can perform the stage and every option has an associated cost and time. Hence, the problem is to select an option per stage that minimises the safety stock and lead time at the same time. We proposed solving the problem using two swarm intelligent meta-heuristics, Ant Colony and Intelligent Water Drop, because of their results in solving NP-hard problems such as the safety stock problem. In our proposed algorithm, swarms are created and each one selects an option per stage with its safety stock and lead time. After that, the Pareto Optimality Criterion is applied to all the configurations to compute a Pareto front. A real-life logistic network of the automotive industry is solved using our proposed algorithm. Finally, we provided some multi-objective performance metrics to assess the performance of our approach and carried out a statistical analysis to support our conclusions.Asociación Mexicana Cultura, A.C. As part of the National Research Network “Sistemas de Transporte y Logística”, the authors acknowledge all the support provided by the National Council of Science and Technology of Mexico (CONACYT) through the research program “Redes Temáticas de Investigación

Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design

This paper proposes a new approach to determining the Supply Chain (SC) design for a family of products comprising complex hierarchies of subassemblies and components. For a supply chain, there may be multiple suppliers that could supply the same components as well as optional manufacturing plants that could assemble the subassemblies and the products. Each of these options is differentiated by a lead-time and cost. Given all the possible options, the supply chain design problem is to select the options that minimise the total supply chain cost while keeping the total lead-times within required delivery due dates. This work proposes an algorithm based on Pareto Ant Colony Optimisation as an effective meta-heuristic method for solving multi-objective supply chain design problems. An experimental example and a number of variations of the example are used to test the algorithm and the results reported using a number of comparative metrics. Parameters affecting the performance of the algorithm are investigated.Supply chain configuration Multi-objective optimisation Ant colony Meta-heuristics

Assessing by Simulation the Effect of Process Variability in the SALB-1 Problem

The simple assembly line balancing (SALB) problem is a significant challenge faced by industries across various sectors aiming to optimise production line efficiency and resource allocation. One important issue when the decision-maker balances a line is how to keep the cycle time under a given time across all cells, even though there is variability in some parameters. When there are stochastic elements, some approaches use constraint relaxation, intervals for the stochastic parameters, and fuzzy numbers. In this paper, a three-part algorithm is proposed that first solves the balancing problem without considering stochastic parameters; then, using simulation, it measures the effect of some parameters (in this case, the inter-arrival time, processing times, speed of the material handling system which is manually performed by the workers in the cell, and the number of workers who perform the tasks on the machines); finally, the add-on OptQuest in SIMIO solves an optimisation problem to constrain the cycle time using the stochastic parameters as decision variables. A Gearbox instance from literature is solved with 15 tasks and 14 precedence rules to test the proposed approach. The deterministic balancing problem is solved optimally using the open solver GLPK and the Pyomo programming language, and, with simulation, the proposed algorithm keeps the cycle time less than or equal to 70 s in the presence of variability and deterministic inter-arrival time. Meanwhile, with stochastic inter-arrival time, the maximum cell cycle is 72.04 s. The reader can download the source code and the simulation models from the GitHub page of the authors

Minimising safety stock and lead time in production systems under guaranteed-service time models by swarm intelligence

In this chapter, we address the problem of placing safety and in-transit inventory over a multi-stage manufacturing supply chains (SC) in which one or more products are manufactured, subject to a stochastic demand . The first part of the problem is to configure the SC given that manufacturers have one or more options to perform every supplying, assembly, and delivery stage. Then, a certain amount of inventory should be placed on each stage to ensure products are delivered to customers just in the stages' service time. We tested a new nature-inspired swarm-based meta-heuristic called Intelligent Water Drop (IWD) which imitates some of the processes that happen in nature between the water drops of a river and the soil of the river bed. The proposed approach is based on the creation of artificial water drops, which adapt to their environment to find the optimum path from a river/lake to the sea. This idea is embedded into our proposed algorithm to find the cheapest cost of supplying components, assembling, and delivering products subject to the stages' service time. We tested our approach using four instances, used widely as test bed in literature. We compared the results computed to the ones computed by Ant Colony Meta-heuristic and provided some metrics as well as graphical results of the outputs

Time and space resolved optical emission diagnostics of laser induced breakdown muscle tissue samples

XXIV Reunión Nacional de Espectroscopia-VIII Congreso Ibérico de Espectroscopia ; organizan Sociedad de Espectroscopia Aplicada (SEA) y la Universidad de la Rioja. P100The recent progress made in developing laser-induced breakdown spectroscopy (LIBS) has transformed this technique from an elemental analysis method to one that can be applied for the analysis of complex biological material or clinical specimens. The LIBS method has gained a reputation as a flexible and convenient technique for rapidly identification of unknown materials (chemical, biological or explosive). The plasma generated by LIBS technique on muscle tissue samples [1] was investigated using two high-power pulsed lasers (transverse excitation atmospheric CO2 and Nd:YAG lasers). A remarkable fact is the no influence of the laser wavelength on the observed spectral lines and molecular bands. The emission of the plasma shows excited neutral Na, K, C, Mg, H, N and O atoms, ionized C+, C2+, Mg+, N+ and O+ species and molecular band systems of CN(B2¿+ ¿ X2¿+), C2(d3¿g ¿ a3¿u), CH(A2¿ ¿ X2¿), NH(A3¿ ¿ X3¿-) and OH(A2¿ ¿ X2¿). For the assignment of the atomic/ionic lines we used the information tabulated in NIST [2]. The molecular bands were compared with the LIBS experiments obtained in our laboratory on different samples [3-6]. We focus our attention on the dynamics of the muscle tissue laser induced plasma species expanding into air (atmospheric pressure) or into vacuum (air pressures of 0.8 and 0.01 Pa). In conventional one dimensional optical emission spectroscopy (OES) studies, various plasma-plume segments were selected along the plume expansion axis and averaged over line-of-sight. This setup was easily transformed to a two-dimensional (2D) OES setup [7] by inserting a Dove prism between the focusing and collimating lenses. Time-integrated and time-resolved 2D OES plasma profiles were recorded as a function of emitted wavelength and distance from the target. Different plasma parameters such as velocities, temperatures and electron densities were evaluated using OES. The temporal behaviour of specific lines of atomic/ionic lines was characterized.This work was partially supported by the MICINN (Spain, Ministerio de Ciencia e Innovación), project CTQ2010-15680, Autónoma University of Madrid, project CEMU-2012-003 and Complutense University of Madrid, grant CCG10-UCM/PPQ-4713.Peer Reviewe