The quay crane scheduling problem is a core task of managing maritime container terminals. From this planning problem arise two decisions to be made: The first one concern the assignment of tasks to quay crane and the second one consist on finding the handling sequence of tasks such that the turnaround time of cargo vessels is minimized. In this paper, we focus our attention on the assignment of tasks to quay cranes, which is considered NP-complete problem. So we propose a meta-heuristic approach based on the ant behavior which is named the Ant Colony Optimization (ACO). This approach takes into account spatial constraint for the resolution of this problem. Finally, we provide a comprehensive numerical result in order to show the performance of our method.

The concept of diabatic distillation is applied to an extractive distillation system of ethanol, which uses glycerol as entrainer, to study the influence of heat flows in optimal design, operation, and thermodynamic efficiency of such systems via exergy analysis. First, optimal operating conditions for minimum exergy losses are computed for a diabatic column with fixed feed locations and number of trays. Then, optimal design (feed locations, number of trays, and heat flows along the column) and operation of the system is calculated as a mixed integer nonlinear programming (MINLP) problem, for an economic and economic-exergetic objective functions for two different entrainer molar flows. It was found that the entrainer molar flow has remarkable influence in the reduction of the exergy losses of the system.

The present study aims to figure out the drivers and motives behind merger and acquisitions (M&As) and their effects in the post-M&As scenarios, considering the case study of the acquisition of HK Express by Cathay Pacific in 2019. First, commercial situational analysis of four Hong Kong-based airlines has been done to understand the current and future scenarios. To identify the drivers behind M&As, several quantitative and qualitative research methods and techniques have been used such as interviews, collection, and analysis of market share data, on-time performance data, etc. These data are analyzed through linear regression, paired T-test, etc. We analyzed the case of Cathay Pacific acquisition in three steps: pre-acquisition stage, peri-acquisition stage, and post-acquisition stage. A total of 8 drivers of airline acquisition have been identified. They include weakening of the acquiree, strengthening of the acquirer, financial situation of the acquiree, compatibility of network, compatibility of business model, concerns of airport slots, branding of acquiree and external business environment. To examine the changes and effects of M&As, an improved Fishcer and Platzer model is used to study dimensions of post-merger effects. We figure out 5 different dimensions of effects brought by the acquisition including operational services, investor confidence, internal confidence, possible structural changes of the Cathay Group, and the possible changes towards the external business environment. This study may serve as a useful reference for relevant stakeholders.

"Networks are mathematically directed (in practical applications also undirected) graphs and a graph is a one-dimensional abstract complex, i.e., a topological space. Network theory focuses on various topological structures and properties, dynamic properties, and functionality-topology relationship, etc. There are some common mathematical foundations, theories and methodology for network analysis, in which graph theory, statistics, and operational research, etc., are the fundamental sciences of network analysis. Various emerging biological networks, at both micro- and macro- levels, will provide numerous sources for the development of general network theory and methodology and also facilitate the development of theory and methodology of biological networks.

Biological network analysis is a fast moving science. Many core scientific issues, for example, ecological structure, co-evolution, co-extinction and biodiversity conservation in ecology, and cancer development and metabolic regulation in health science, etc., are expected to be addressed by network approaches and network analysis. Network analysis is becoming the core methodology to treat complex biological systems. As the fast development of this area, more and more papers on biological networks are published.

At present explosive numbers of quality papers on biological networks are being published each year. The initiation of the journal, Network Biology, will provide a public and unified platform for the publication of these studies. From this integrated and unique journal, researchers, university teachers and students will thoroughly have an in-depth and complete insight on knowledge, methodology and recent advances of biological networks.

In the view of system dynamics, biological networks are always self-organized systems with emergent, autonomous and adaptive properties. Their dynamics can be represented by agent-based modeling, individual-based modeling and some other methodologies like neural network modeling. Therefore, agent-based modeling, individual-based modeling, self-organization of biological systems, and neural network modeling, etc., fall into the aims and scope of the journal, Network Biology.

The NETWORK BIOLOGY (ISSN 2220-8879) is an open access, peer-reviewed online journal that considers scientific articles in all different areas of network biology. It is the transactions of the International Society of Network Biology.It dedicates to the latest advances in network biology. The goal of this journal is to keep a record of the state-of-the-art research and promote the research work in these fast moving areas. The topics to be covered by Network Biology include, but are not limited to:

•Theories, algorithms and programs of network analysis
•Innovations and applications of biological networks
•Dynamics, optimization and control of biological networks
•Ecological networks, food webs and natural equilibrium
•Co-evolution, co-extinction, biodiversity conservation
•Metabolic networks, protein-protein interaction networks, biochemical reaction networks, gene networks, transcriptional regulatory networks, cell cycle networks, phylogenetic networks, network motifs
•Physiological networks
•Network regulation of metabolic processes, human diseases and ecological systems
•Social networks, epidemiological networks
•System complexity, self-organized systems, emergence of biological systems, agent-based modeling, individual-based modeling, neural network modeling, and other network-based modeling, etc.
We are also interested in short communications that clearly address a specific issue or completely present a new ecological network, food web, or metabolic or gene network, etc.

Authors can submit their works to the email box of this journal, networkbiology@iaees.org. All manuscripts submitted to this journal must be previously unpublished and may not be considered for publication elsewhere at any time during review period of this journal. Authors are asked to read Author Guidelines before submitting manuscripts.

In addition to free submissions from authors around the world, special issues are also accepted. The organizer of a special issue can collect submissions (yielded from a research project, a research group, etc.) on a specific research topic, or submissions of a scientific conference for publication of special issue.

Network Biology 
ISSN 2220-8879
URL: http://www.iaees.org/publications/journals/nb/online-version.asp
RSS feed: http://www.iaees.org/publications/journals/nb/rss.xml
E-mail: networkbiology@iaees.org
Editor-in-Chief: WenJun Zhang"

In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). The fundamental concepts and ideas of MBA are derived from the explosion of mine bombs in real world. The efficiency of the proposed optimizer is tested via the optimization of several truss structures with discrete variables and its performance is compared with several well-known metaheuristic algorithms. The results show that MBA is able to provide faster convergence rate and also manages to achieve better optimal solutions compared to other efficient optimizers.

This paper aims to present an implementation of classical DEA models in R, a free software and open source, highly extensible that offers a variety of functions and graphical routines for data analysis. In this work we show both the CRS and VRS DEA models. The computational implementation is illustrated with real data from the Brazilian electric power distribution utilities.

Companies exist not just for the provision of goods and services but to maximize profits and drive wealth to their owners. As that is what guarantees its continuous existence, productivity and expansion. The lack of effective and sustainable profit maximization results in the liquidation of organizations, especially the small scale production companies. This work demonstrates the pragmatic use of linear programming methods in maximization of profit at Johnsons Nig. Ltd, Bakery division wherein the four various Kings Size bread were subjected to statistical analysis via the Simplex method in a bid to determine which bread size assures more objective value contribution and gives maximum profit at a given level of production capacity. The optimal solution obtained showed that the production of three units of large Kings bread size with the objective coefficient of fifty naira will yield an objective value contribution of One hundred and fifty naira. To test the feasibility of the solution, Sensitivity analysis was carried out, the result of which revealed that for the optimal solution to remain comparatively unchanged the coefficient of í µí±¥ must remain between 50 to 30. Otherwise, its contribution to profit will be zero, which will in turn necessitate its discontinuity.

Scheduling of tasks is one of the main concerns in the Cloud Computing environment. The whole system performance depends on the used scheduling algorithm. The scheduling objective is to distribute tasks between the Virtual Machines and balance the load to prevent any virtual machine from being overloaded while other is underloaded. The problem of scheduling is considered an NP-hard optimization problem. Therefore, many heuristics have been proposed to solve this problem up to now. In this paper, we propose a new Spider Monkeys algorithm for load balancing called Spider Monkey Optimization Inspired Load Balancing (SMO-LB) based on mimicking the foraging behavior of Spider Monkeys. It aims to balance the load among virtual machines to increase the performance by reducing makespan and response time. Experimental results show that our proposed method reduces tasks' average response time to 10.7 seconds compared to 24.6 and 30.8 seconds for Round Robin and Throttled methods respectively. Also, the makespan was reduced to 21.5 seconds compared to 35.5 and 53.0 seconds for Round Robin and Throttled methods respectively.

Corporate performance is  measurable by its  activities of which is supported by the  industrial performance through the Optimization in targeted profit. PT. Argo Pantes is a manufacturing company which processes yarn and woven fabric. In the daily process the company has many problems or constrains in production planning. Uncertaintly demand of goods fluctuation has effect on shortage or Surplus production. Others problems are raw  materials, machine work hour, labour work hour, spindle hour per unit, Loom hour per unit, and the demand of the  products. The objective of this research is  to maximize a business profit by using the application of linear programming. Simplex method of Linear programming purposes to maximize  profit in linear function.  Profit (Z) = 20 X1 + 15 X2 and linear function of the two constrains, Spindle hour per unit: 100 X1 + 50. X2 ≤ 1000 and  Loom hour per unit: 20 X1 5 X2 ≤ 300. The Total profit earned  by PT. Argo Pantes at Tangerang to produce a T/C woven fabric is $133.400, and for cotton 100% woven fabric is $100.050 with the assumtion of profit is in accordance with  fixed  objective  and  constrain  function.