Reducing CO2 emission from exhaust gases using molten carbonate fuel cells: a new approach

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO₂ from gas turbine exhaust gases that have CO₂ emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO₂ emission rate. Objective functions of the second scenario are the same as in the first scenario while CO₂ tax is taken into account. Results show that the second scenario has 29.5% lower average optimal COE and 2.5% lower average emission rate in comparison with the first scenario. A sensitivity analysis is also performed to study the effect of fuel price and CO₂ tax variations on optimal solutions.     

A comparison of five hybrid metaheuristic algorithms for unrelated parallel-machine scheduling and inbound trucks sequencing in multi-door cross docking systems

The objective of this paper is to develop five hybrid metaheuristic algorithms, including three hybrid ant colony optimization (hACO) variants, and compare their performances in two related applications: unrelated parallel machine scheduling and inbound truck sequencing in a multi-door cross docking system in consideration of sequence dependent setup, and both zero and nonzero release time. The three hACO variants were modified and adapted from the existing literature and they differ mainly in how a solution is coded and decoded, how a pheromone matrix is represented, and the local search methods employed. The other two hybrids are newly constructed hybrid simulated annealing (hSA) algorithms, which are built based on the authors’ knowledge and experience. The evaluation criteria are computational time and the objective function value, i.e., makespan. Based on the results of computational experiments the simulated annealing-tabu search hybrid turns out to be the best if maximal CPU time is used as the stopping criterion and the 2-stage hACO variant is the best if maximal number of evaluations is the stopping criterion. The contributions of this paper are: (i) being the first to carry out a comparative study of hybrid metaheuristics for the two selected applications, (ii) being the first to consider nonzero truck arrival time in multi-door cross docking operations, (iii) identifying which hACO variant is the best among the three, and (iv) investigating the effect of release time on the makespan.     

A modified ant colony system for finding the expected shortest path in networks with variable arc lengths and probabilistic nodes

The problem of finding the expected shortest path in stochastic networks, where the presence of each node is probabilistic and the arc lengths are random variables, have numerous applications, especially in communication networks. The problem being NP-hard we use an ant colony system (ACS) to propose a metaheuristic algorithm for finding the expected shortest path. A new local heuristic is formulated for the proposed algorithm to consider the probabilistic nodes. The arc lengths are randomly generated based on the arc length distribution functions. Examples are worked out to illustrate the applicability of the proposed approach.     

Effect of hybridizing Biogeography-Based Optimization (BBO) technique with Artificial Immune Algorithm (AIA) and Ant Colony Optimization (ACO)

Hybridization in optimization methods plays a very vital role to make it effective and efficient. Different optimization methods have different search tendency and it is always required to experiment the effect of hybridizing different search tendency of the optimization algorithm with each other. This paper presents the effect of hybridizing Biogeography-Based Optimization (BBO) technique with Artificial Immune Algorithm (AIA) and Ant Colony Optimization (ACO) in two different ways. So, four different variants of hybrid BBO, viz. two variants of hybrid BBO with AIA and two with ACO, are developed and experimented in this paper. All the considered optimization techniques have altogether a different search tendency. The proposed hybrid method is tested on many benchmark problems and real life problems. Friedman test and Holm–Sidak test are performed to have the statistical validity of the results. Results show that proposed hybridization of BBO with ACO and AIA is effective over a wide range of problems. Moreover, the proposed hybridization is also effective over other proposed hybridization of BBO and different variants of BBO available in the literature.     

乳清发酵酒消毒技术研究及其应用

乳清发酵酒产品是近年来发展起来的新产品。在生产实践中,公司试验研究了乳清发酵酒生产工艺中的消毒技术,按工艺流程的先后顺序,研究了原料消毒、生产环境消毒、生产设备消毒等内容。生产实践证明,这些方法或技术措施的运用,保证了乳清发酵酒的品质,且口味纯正、质量稳定。主要阐述了乳清发酵酒生产过程的消毒技术和措施。     

分布式工作流管理系统中的一种资源搜索策略

针对分布式工作流管理系统中的资源搜索问题，提出一种新的搜索策略。该方法利用聚类算法将网分簇管理，使得查找过程中的逻辑拓扑和物理拓扑相互匹配，在此基础上采用结合了兴趣度的蚁群算法提供查找线索。实验表明，该方法提高了工作流引擎服务的整体响应时间，在查找成功率、平均响应时间和平均消息数上较泛洪查找和传统蚁群算法都更具优势。     

Process optimisation and physicochemical characterisation of enzymatic hydrolysates of proteins from co‐products of Atlantic Salmon (Salmo salar) and Yellowtail Kingfish (Seriola lalandi)

The aim of this study was to develop an enzymatic hydrolysis process of protein co‐products for two major commercial fish species in Australia: Atlantic salmon (AS) and Yellowtail kingfish (YTK). The outcomes are to produce high protein recovery of fish protein hydrolysates within controlled molecular weight ranges that display enhanced physicochemical properties of oil binding and emulsification. Three enzymes (Flavourzyme, Neutrase and Alcalase) were applied to processing co‐products. Protein recovery and physicochemical properties were evaluated with increasing hydrolysis time from 30 min to 180 min and ratio of enzyme to substrate (E/S) from 0.5% to 3.0%. In order to achieve a product with optimum emulsifying capacity (50 ± 0.6 m² g^?1), an E/S ratio of 0.6–1.3% Flavourzyme was applied for 30–111 min with a protein recovery of 55%; in order to achieve a product with optimum oil‐binding capacity (8.3 ± 0.3 g oil g hydrolysates^?1), an E/S ratio of 2.3–3.0% Flavourzyme was applied for 25–64 min with a protein recovery of 70%. YTK protein hydrolysates were further membrane‐fractionated into five fractions (>100 kDa, 50–100 kDa, 30–50 kDa, 10–30 kDa and <10 kDa), and of these, the 10–30 kDa exhibited the best properties of oil binding (19 ± 0.3 g oil g hydrolysates^?1) and emulsification (57 ± 0.7 m² g^?1). These results demonstrate the importance of enzymatic hydrolysis of seafood co‐products into high‐value ingredients for food products and processing.     

A comparative study on optimised and non‐optimised axial flow,spherical reactors in naphtha reforming process

In this study, the operating conditions of an axial flow spherical reactor have been optimised using a reliable optimisation technique and the results are compared with the results of non‐optimised conditions. The dynamic behaviour of the reactor has been considered in the optimisation process and orthogonal collocation method has been used in order to solve the obtained equations from mathematical modelling of the process. The goal of this study is to maximise the aromatics and hydrogen production rate. Therefore, the objective function is the combination of two terms which include the production rate of the mentioned components. The catalyst distribution for each reactor, the inlet pressure of the system, Length per radius for each reactor, the naphtha feed molar flow rate and the hydrogen mole fraction in the recycle stream as well as the inlet temperature of each reactor have been optimised in this study. © 2011 Canadian Society for Chemical Engineering     

Robust eigenstructure clustering by non-smooth optimisation

We extend classical eigenstructure assignment to more realistic problems, where additional performance and robustness specifications arise. Our aim is to combine time-domain constraints, as reflected by pole location and eigenvector structure, with frequency-domain objectives such as the H₂, H_∞ or Hankel norms. Using pole clustering, we allow poles to move in polydisks of prescribed size around their nominal values, driven by optimisation. Eigenelements, that is poles and eigenvectors, are allowed to move simultaneously and serve as decision variables in a specialised non-smooth optimisation technique. Two aerospace applications illustrate the power of the new method.     

Scheduling of open-pit phosphate mine extraction

Open-pit deposits are often characterised by a stack of layers of different geological nature. Some layers are worthless while the ore of the others is of a varying economic value depending on grade. To reach a layer, it is necessary to have first removed the upper layers above the extraction zone. This action results in uncovering the layer in this particular place and in facilitating access to the layers below. This extraction process involves a series of 2–7 basic operations; each one is performed by a machine, some of which are able to perform up to three different operations. Ensuring the consistency of mining extraction scheduling over a few months, in order to meet known or forecast demand, is a challenging task. A mining extraction model based on mathematical programming is proposed but it is hardly usable, due to its size. Therefore, a model based on a Discrete Event Simulation, is created to test how ore supplies are affected by the tactical and operational decisions relating to the choice of parcels to be processed and to the allocation of machines to the different basic operations.