Deadlock Situations Research Articles

Achieving Effective International Cooperation: How Institutional Formalization Shapes Intergovernmental Negotiations

This article explores how formalization of institutions and domestic constraints influence the outcomes of international cooperation and negotiation processes—particularly in a regional setting like the European Union (EU) or the Association of Southeast Asian Nations (ASEAN). Examining different forms of institutional setup along the formal‐informal continuum, this study evaluates their impact on the successes and failures of intergovernmental negotiation processes. While some scholars have been vocal about the importance of institutional setting on negotiation outcomes, there has not yet been any systematic analysis of the impact of institutional variations on the actual negotiation process. This project specifies under what conditions domestic actors constrain governments, and how these conditions depend on institutional structures. I analyze the impact of institutional variations, concentrating on negotiation failure and deadlock situations, to form a framework that can differentiate between various bargaining situations and to understand their impact on the possibility to facilitate successful negotiation outcomes. The central argument highlights the need for more nuanced connections between institutional design, domestic constraints, and the level of formalization to understand the likelihood of success or failure of intergovernmental negotiation processes.

Ten Diverse Formal Models for a CBTC Automatic Train Supervision System

Communications-based Train Control (CBTC) systems are metro signalling platforms, which coordinate and protect the movements of trains within the tracks of a station, and between different stations. In CBTC platforms, a prominent role is played by the Automatic Train Supervision (ATS) system, which automatically dispatches and routes trains within the metro network. Among the various functions, an ATS needs to avoid deadlock situations, i.e., cases in which a group of trains block each other. In the context of a technology transfer study, we designed an algorithm for deadlock avoidance in train scheduling. In this paper, we present a case study in which the algorithm has been applied. The case study has been encoded using ten different formal verification environments, namely UMC, SPIN, NuSMV/nuXmv, mCRL2, CPN Tools, FDR4, CADP, TLA+, UPPAAL and ProB. Based on our experience, we observe commonalities and differences among the modelling languages considered, and we highlight the impact of the specific characteristics of each language on the presented models.

TOPSIS Approach for Solving Bi-Level Non-Linear Fractional MODM Problems

TOPSIS (technique for order preference similarity to ideal solution) is considered one of the known classical multiple criteria decision making (MCDM) methods to solve bi-level non-linear fractional multi-objective decision making (BL-NFMODM) problems, and in which the objective function at each level is considered nonlinear and maximization type fractional functions. The proposed approach presents the basic terminology of TOPSIS approach and the construction of membership function for the upper level decision variable vectors, the membership functions of the distance functions from the positive ideal solution (PIS) and of the distance functions from the negative ideal solution (NIS). Thereafter a fuzzy goal programming model is adopted to obtain compromise optimal solution of BL-NFMODM problems. The proposed approach avoids the decision deadlock situations in decision making process and possibility of rejecting the solution again and again by lower level decision makers. The presented TOPSIS technique for BL-NFMODM problems is a new fuzzy extension form of TOPSIS approach suggested by Baky and Abo-Sinna (2013) (Applied Mathematical Modelling, 37, 1004-1015, 2013) which dealt with bi -level multi-objective decision making (BL-MODM) problems. Also, an algorithm is presented of the new fuzzy TOPSIS approach for solving BL-NFMODM problems. Finally, an illustrative numerical example is given to demonstrate the approach.

Implementing Industry 4.0 in Discrete Manufacturing: Options and Drawbacks

The Industry 4.0 concept embodies a topic widely discussed during specialized meetings and tutorials. Originally, this approach was interpreted as an attempt to shift industrial processes towards establishing the fully digitized smart factory; at present, however, it already exerts an influence on many other fields and disciplines. In this article, the concept is described from the perspective of discrete manufacturing. The implementation possibilities are outlined, with options such as the Asset Administrative Shell or Consumer-Provider model introduced in greater detail. We also mention some drawbacks to implementing job shop scheduling as provided by the latter option; these disadvantages include, for instance, the deadlock situation. Some methods to solve the problem are demonstrated to facilitate well-balanced presentation. A job shop scheduling algorithm using the AAS is also addressed, and a new evaluation function is proposed.

Optimization of the transfer function through handling productivity control in port container terminals

This paper investigates the efficiency of different models in shaping the transfer function of port container terminals by coordinating the handling equipment’s activity. Differences in the productivity of the handling equipment and the limited capacity of the storage area at berth generate deadlock situation that could be handle through three correlation procedures: (i) adjusting the productivity to the minimum when the storage area is fully used; (ii) on/off control of the most efficient equipment, and (iii) limitation of the productivity of the most performing equipment. These techniques and the variations in input elements (ships arrival rate, containers number to unload/load, berth storage area) are taken into account for choosing the best strategy of port activity. A simulation model, developed with ARENA software, is created to analyse the port activity. Beyond the analytical models that deal with one ship handling process, the simulation model could take into consideration the process on a period of time, allowing studying the impact of stochastic elements on the process. The model contains the following modules: the vessels arrival, waiting in harbour, anchorage, containers unloading/loading on the vessels, temporary storage at berth, container transfer to inland storage area, and vessel departure. Computer simulations allow analysing random variable of the vessels time spent in port. The mean value should be kept at minimum and thus the best handling strategy could be identified. In addition, the sensitivity of the results according to the variation of the input elements is obtained.

아베 수상의 대러 새로운 접근 : 공동경제활동을 중심으로

At the summit held in Japan in December 2016, the leaders of both countries agreed to advance to the common goal of peace treaty by actually contributing to the development of the four islands of conflict and improving the lives of the people through joint economic activities at the based on the 「new approach」. Both leaders also agreed to expand the free visit for the people who was lived the islands.BR Thus, Japanese Prime Minister Abe intends to transform the island into the same island that was returned through the joint economic activities and freedom of free visits in the islands. In this way, he wants to draw the future of the disputed island first. And Japanʹs proposal is to carry out the joint economic activities in the conflict four islands under the 「special system」 which does not impair the legal position of both sides. It is already over a year, but the working‐level meetings of the two countries on ʺspecial systemʺ are being held, they are not making progress on the specific discussion.BR In order not to take past experience, activities under the 「special system」 said by Prime Minister Abe are necessary. In the press announcement after the summit meeting, it is said that it will be carried out by the governments of both countries under the 「international promise」. As such, they agreed to pursue joint economic activities in a way that does not hinder each otherʹs position. This is an unique approach for the future. Joint economic activities on conflict islands should not violate each otherʹs sovereignty. And if they create a framework like ʺlegal joint managementʺ and work under it, they will be able to breathe new winds into the territory negotiations in deadlock situation. This will lead to the coexistence of the two countries on this disputed island.BR Therefore, the two countries need to create a system of coexistence and co‐prosperity in a way that does not interfere with the otherʹs position. With this approach, the two countries should accumulate confidence in the disputed islands. If we can proceed to the peace treaty in this way, the Abe administrationʹs Russian policy can be said to be a good start towards a stable peace treaty.BR In this paper I would like to look at Abeʹs new approach to Russia from three aspects. First, what is 「a new approach」 to Prime Minister Abeʹs new policy on Russia, what are the 8 items of economic cooperation plans and how are they being pursued? Second, I will look at the historical progress and meaning of joint economic activities on the disputed islands, and the progress of field surveys and free visits by former residents. Thirdly, I will try to analyze the issues and prospects of joint economic activities under the 「special system」 which does not impair the legal position of both sides.

Solving Multi-level Multi-objective Fractional Programming Problems with Fuzzy Demands via FGP Approach

This paper presents a fuzzy goal programming approach for solving multi-level multi-objective fractional programming problem with fuzzy demands. It makes an extension work of Pal et al. (Fuzzy Sets Syst 139(2):395–405, 2003). Firstly, the concept of $$\alpha $$ -cut is applied to transform the fuzzy mathematical problem into a common deterministic one. Then, the membership functions for the defined fuzzy goals are developed. Also, in the proposed approach, linearization of membership goals of the objective functions is presented. Secondly, the highest degree of each of these membership goals is achieved by minimizing the sum of the negative deviational variables. Moreover, the final model is simplified by eliminating solution preferences by the decision makers at each level, thereby avoiding decision deadlock situations. Finally, an illustrative numerical examples and comparisons with the existing methods are used to demonstrate the applicability and performance of the proposed approach.

Comparative modelling and verification of Pthreads and Dthreads

AbstractThe POSIX threads (Pthreads) library is a thread API for C/C++ to control parallel threads and spawn concurrent process flows. Programming in Pthreads usually suffers from undesirable deadlock, data race, and race condition problems due to the potential nondeterministic execution behaviors between parallel threads. Dthreads, as another multithreading model that re‐implements Pthreads, was proposed by Liu et al for efficient deterministic multithreading. They found out that, under specific test cases, Dthreads can effectively prevent data races. However, no comparison test has been made with Pthreads.To perform a formal comparison between Pthreads and Dthreads over deadlocks, data races, and race conditions, in this paper, we adopt CSP (communicating sequential processes) as a formal model for specifying part of API functions in Pthreads and Dthreads and illustrate the model construction using 4 classical example programs. By feeding the models into the model checker PAT (process analysis toolkit), we have verified that deadlocks and data races exist in Pthreads, but do not exist in Dthreads, for the considered programs. We have also found that neither of them can prevent race conditions. Our comparative modelling and verification of Pthreads and Dthreads show that though Dthreads cannot prevent all the deadlock situations, shown by verification results of another 2 example programs, Dthreads is better than Pthreads on eliminating data races and preventing deadlocks. Considering limited scalability of Dthreads, we have introduced a new programming model to support coarse granularity in bank transfer. Our modelling is also extended by covering the synchronization operations in Liu et al work.

A Model with Traffic Routers, Dynamically Managing Signal Phases to Address Traffic Congestion in Real Time

On-road Vehicular traffic congestion has detrimental effect on three lifelines: Economy, Productivity and Pollution (EPP). With ever increasing population of vehicles on road, traffic congestion is a major challenge to the economy, productivity and pollution, notwithstanding continuous developments in alternative fuels, alternative sources of energy. The research develops accurate and precise model in real time which computes congestion detection, dynamic signaling algorithm to evenly distribute vehicle densities while ensuring avoidance of starvation and deadlock situation. The model incorporates road segment length and breadth, quality and achievable average speed to compute road capacity. Vehicles installed with GPS enabled devices provide their location, which enables computing road occupancy. Road occupancy is evaluated based on number of vehicles as well as area occupied by vehicles. Ratio of road occupancy and road capacity provides congestion index important to compute signal phases. The algorithm ensures every direction is serviced once during a signaling cycle ensuring no starvation. Secondly, the definition of minimum and maximum signal timings ensures against dead lock situation. A simulator is developed to validate the proposition and proves it can ease congestion by more than 50% which is better than any of the contemporary approaches offering 15% improvement. In case of higher congestion index, alternate routes are suggested based on evaluation of traffic density graphs for shortest route or knowledge database. The algorithm to compute shortest route is optimized drastically, reducing computation cost to 3*√2N vis-a-vis computation cost of N2 by classical algorithms. The proposal brings down the cost of implementation per traffic junction from USD 30,000 to USD 2000.

And/or-convexity: a graph convexity based on processes and deadlock models

Deadlock prevention techniques are essential in the design of robust distributed systems. However, despite the large number of different algorithmic approaches to detect and solve deadlock situations, yet there remains quite a wide field to be explored in the study of deadlock-related combinatorial properties. In this work we consider a simplified AND-OR model, where the processes and their communication are given as a graph G. Each vertex of G is labelled AND or OR, in such a way that an AND-vertex (resp., OR-vertex) depends on the computation of all (resp., at least one) of its neighbors. We define a graph convexity based on this model, such that a set $$S \subseteq V(G)$$ is convex if and only if every AND-vertex (resp., OR-vertex) $$v \in V(G){\setminus }S$$ has at least one (resp., all) of its neighbors in $$V(G) {\setminus } S$$ . We relate some classical convexity parameters to blocking sets that cause deadlock. In particular, we show that those parameters in a graph represent the sizes of minimum or maximum blocking sets, and also the computation time until system stability is reached. Finally, a study on the complexity of combinatorial problems related to such graph convexity is provided.

Virtual Motion Control of an Android Robot Hand Using a Knowledge Base During Synthesis of Movements with Account of the Positions of the Exclusion Zones

The article presents organization of a knowledge base required for implementation of the intelligent control of the movement of an android robot hand with account of the positions of the exclusion zones. The proposed structure of the knowledge base characterizes the previous experience of the synthesis of the hand movements by the velocity vector with account of the known obstacles, and sets the properties intrinsic to them. The knowledge base consists of four components. The first one specifies the images, which represent a projection of the contours of the working areas of the mechanism, taking into account the exclusion zones. The second one stores configurations with the maximal values of the parameters, which define the solid angle, used to calculate the most optimal initial set position with respect to an object of manipulation. The third one cmoanxtains configurations of the movement, from which a deadlock situation results. The fourth one sets the maximal values of kimax parameters. The fourth component of the knowledge is necessary to reduce the time of calculation of the vector of the generalized velocities, when the calculated configuration crosses the exclusion zone. The algorithm of the virtual motion control of a robot android organized on the knowledge base allows us to implement the methods for evaluation of the current situation and make respectively one or another logical choice. The results of the computational experiments show a reduction of time for calculation of the test tasks associated with setting and removal of the manipulation objects on the shelves and racks with the use of the developed knowledge base.

Decentralized Hybrid Control for Multi-Agent Motion Planning and Coordination in Polygonal Environments

This paper presents a decentralized hybrid control scheme for the motion planning and coordination of teams of mobile agents in known obstacle environments with both convex and non-convex obstacles. A mathematical analysis using tools from switched systems theory is carried out to establish the convergence of the system trajectories under certain modeling assumptions on the surrounding environment. The design resolves a class of deadlock situations arising in earlier work, and allows for a wider class of obstacles (both convex and non-convex) to be considered in the environment. Simulation results demonstrate the efficacy of the algorithm.

When the farm-gate becomes a revolving door: An institutional approach to high labour turnover

By adopting an institutional theory lens, the aim of the article is to better understand the actions and mindset of managers toward high labour turnover in the cut-flower industry in Ethiopia. Our mixed-method approach explores the ways in which managers deal with, and legitimize, high levels of labour turnover. Our results show that they engage in three types of practices – predicting, containing and accommodating – whose objective is to make labour turnover tolerable, rather than reduce it. Interestingly, managers do not legitimize their practices through the use of cost-benefit arguments, as the literature would have suggested, but blame the institutional context. This article highlights the context-dependent aspects of labour turnover and explains how managers may find themselves in a deadlock situation. It informs the debate in human resource management research about managerial practices at the bottom of global value chains.

Distributed iterative command governor schemes for interconnected linear systems

SummaryA novel distributed command governor (CG) supervision strategy relying on iterative optimization procedure is presented for multi‐agent interconnected linear systems subject to pointwise‐in‐time set‐membership coordination constraints. Unlike non‐iterative distributed CG schemes, here all agents undertake several optimization iterations and data exchange before arriving to the optimal solution. As a result, these methods are able to achieve Pareto‐optimal solutions not only in steady‐state conditions as the ones based on non‐iterative optimization procedures but also during transients and are not hampered by the presence of undesirable Nash‐equilibria or deadlock situations. The main properties of the method are fully investigated and in particular its optimality, stability, and feasibility properties rigorously proved. A final example is presented where the proposed distributed solution is contrasted with existing centralized and distributed non‐iterative CG solutions. Copyright © 2017 John Wiley & Sons, Ltd.

Coastal Areas Division and Coverage with Multiple UAVs for Remote Sensing.

This paper tackles the problems of exact cell decomposition and partitioning of a coastal region for a team of heterogeneous Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the field of view or sensing radius of the sensors on-board. An initial sensor-based exact cell decomposition of the area aids in the partitioning process, which is performed in two steps. In the first step, a growing regions algorithm performs an isotropic partitioning of the area based on the initial locations of the UAVs and their relative capabilities. Then, two novel algorithms are applied to compute an adjustment of this partitioning process, in order to solve deadlock situations that generate non-allocated regions and sub-areas above or below the relative capabilities of the UAVs. Finally, realistic simulations have been conducted for the evaluation of the proposed solution, and the obtained results show that these algorithms can compute valid and sound solutions in complex coastal region scenarios under different setups for the UAVs.

The use of creative techniques in the engineering human resources development

Starting from the role of new technologies in the development of engineering innovation, this paperwork has two main research directions with respect to creativity and innovation in engineering education. These are based on a combination of creative techniques with traditional engineering education methods. The first component of our research presented herein aims the use of creative methods such as Creative Training and Image Streaming, and the second component of the research statistically analyses the Social Media posts regarding the use of Cloud Computing technology as a support for innovation. The aim of combining such lines of research will lead to the emergence of specific knowledge needed to identify and implement new creative techniques in engineering human resources. Applying such creativity techniques within groups of students can result in innovative ideas usable in ongoing research projects, in certain deadlock situations on finding critical solutions to overcome blockages.

A real-time immune planning algorithm incorporating a specific immune mechanism for multi-robots in complex environments

To solve the real-time path planning of multi-robots in complex environments, a new immune planning algorithm incorporating a specific immune mechanism is presented. In the immune planning algorithm incorporating a specific immune mechanism, a new coding format for an antibody is first defined according to the impact of the obstacle distribution on the obstacle avoidance behaviors of multi-robots. Then, a new robot immune dynamic model for antibody selection is designed in terms of different impacts of obstacles and targets on robot behaviors. Finally, aiming at the local minimum problem in complex environments and inspired by the specific immune mechanism, a series of appropriate avoidance behaviors are selected through the calculation of a specific immune mechanism to help robots walk out of local minima. In addition, to solve deadlock situations, a learning strategy for the antibody concentration is presented. Compared with four related immune planning algorithms—an improved artificial potential field, a rapidly exploring random tree algorithm, a D* algorithm and a A* algorithm—the simulation results in four static environments show that the paths planned by immune planning algorithm incorporating a specific immune mechanism are the shortest and the path smoothness is generally the highest, which shows its strong planning capability in multi-obstacle environments. The simulation result in a dynamic environment with local minima shows that the immune planning algorithm incorporating a specific immune mechanism has strong planning ability in dynamic obstacle avoidance and in escaping from local minima. Additionally, an experiment in a multi-robot environment shows that two robots can not only avoid static obstacles but also avoid dynamic obstacles, which further supports the validity of the proposed immune planning algorithm incorporating a specific immune mechanism for multi-robots in real environments.

On fuzzy goal programming procedure to bi-level multiobjective linear fractional programming problems

In this paper, we propose an alternate modified solution procedure based on fuzzy goal programming (FGP) approach for solving bi-level multiobjective linear fractional programming problems (BL-MOLFPPs) with some major modifications in the algorithm suggested by Abo-Sinna and Baky (2010). The proposed modified technique is simpler and requires less computational works than that of earlier technique. In the formulation of FGP models, each objective function (at both the levels - leader's level and follower's level) as well as control variables (of leader's level) are transformed into fuzzy goals with modified membership functions. Then FGP approach is used for achieving the highest degree of each of membership goals. To avoid decision deadlock situations and difficulties associated with bi-level programming problems, solution preferences by decision makers (at leader's and follower's levels) are not taken into account in proposed algorithm. A comparative analysis is also carried out with numerical example in order to show efficiency of proposed algorithm over earlier technique.

Unlocking the Deadlocks? GMOs, Science and the Reform of the Legal Framework

The hydra is in many ways a well-working allegory for the numerous conflicts the EU has been facing in the GMO authorization process, and in particular regarding the complex deadlocks in the authorization of GMOs for cultivation. In the 1990s, heavy pressure at the international level2 caused the responsible EU decision-makers to establish a regulatory framework and the European Food Safety Authority (EFSA) to finally resolve their struggles with the de facto moratorium on GMO authorization. Unfortunately, this solution to the conflicts and struggles with GMO authorization did not prove to be sufficient. Even worse, the EU decision-makers faced what we call the first deadlock. It originated from the continuous bans of GMOs that Member States imposed with the safeguard clause, now in particular on GMO cultivation. As with the Hydra’s many heads which are growing back numerously every time one head is cut off, each time one issue was solved in the GMO authorization process, numerous other problems came up. When over time the new directive and agency proved not be the solution to the many conflicts and as there was no sign that GMO-opposing Member States would finally stop the banning, Member States from both camps – anti- and pro-GMO – instrumentalised the Commission to end the conflict on GMO authorization. The Commission attempted to do so by drafting a proposal,8 which arguably gave the Member States more freedom in deciding whether or not to cultivate GMOs in their territory. Thereby the Commission expected to accelerate the general authorization procedure for GMOs, as anti- GMO Member States could on the one hand agree on authorization of GMOs at the EU level, but also had the opportunity to ban their cultivation on national territory. Irrespective of the Commission’s attempt to solve the conflict and give the Member States more freedom, the proposal did not succeed in solving the deadlock. It was heatedly debated by EU officials and stakeholders, partly amended by the European Parliament (EP) and has not been adopted yet, as a blocking minority in the Council exists. We label this situation the ‘second deadlock’ – namely the deadlock on the solution of the first deadlock. After a couple of years of silence on this situation, the proposal and the whole deadlock situation suddenly became news again, when the Commission announced the revival of the talks and Monsanto, one the biggest GM producing companies, threatened to leave the European market in 2013. GMO authorization in the EU was never an easy topic, partly because the European public is not very fond of the idea of having GM-food on their table. Therefore, not only the heads of the hydra, but also the hydra itself can be compared to the GMO authorization process. In Greece mythology, the hydra was hated by the public as it murdered the farmers’ cattle at night. Unfortunately, up to now there was no Herakles in the EU, being able to find a solution on how to solve the deadlocks in GM- authorization. As there is no complete solution evident at the moment, we investigate to what extent the two deadlocks might be unlocked, also in light of the high prevalence of the topic in the news. Even though we are aware of the manifold aspects surrounding GM-authorization and cultivation, we aim to provide an overview for a broad scholarly public, not only on how the two deadlock arose and what were the exact issues at stake but also regarding the many heads of the hydra – namely the many issues decision-makers need to take into account – when trying to unlock the deadlocks. After explaining our research approach and methodology, our analysis first provides a general overview on the regulatory framework on GMOs. By describing the problems of authorization in practice, we investigate the first deadlock. Subsequently, some of the Hydra’s heads are cut off by means of analysing whether or not science is the solution to the first deadlock. The fourth section presents the Commission’s proposal to solve the deadlock, which is subsequently analysed on its legal viability regarding EU and WTO legislation. It is then attempted to solve the deadlock, or at least to provide some ideas on how to move a step towards solving it. Before concluding, we embed our proposal in the latest state-of-the-art academic literature.

A variable neighbourhood search for fast train scheduling and routing during disturbed railway traffic situations

This paper focuses on the development of metaheuristic algorithms for the real-time traffic management problem of scheduling and routing trains in complex and busy railway networks. This key optimization problem can be formulated as a mixed integer linear program. However, since the problem is strongly NP-hard, heuristic algorithms are typically adopted in practice to compute good quality solutions in a short computation time. This paper presents a number of algorithmic improvements implemented in the AGLIBRARY optimization solver in order to improve the possibility of finding good quality solutions quickly. The optimization solver manages trains at the microscopic level of block sections and at a precision of seconds. The solver outcome is a detailed conflict-free train schedule, being able to avoid deadlock situations and to minimize train delays. The proposed algorithmic framework starts from a good initial solution for the train scheduling problem with fixed routes, obtained via a truncated branch-and-bound algorithm. Variable neighbourhood search or tabu search algorithms are then applied to improve the solution by re-routing some trains. The neighbourhood of a solution is characterized by the set of candidate trains to be re-routed and the available routes. Computational experiments are performed on railway networks from different countries and various sources of disturbance. The new algorithms often outperform a state-of-the-art tabu search algorithm and a commercial solver in terms of reduced computation times and/or train delays.