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Article
Publication date: 9 July 2018

Changjin Xu and Peiluan Li

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying…

Abstract

Purpose

The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Design/methodology/approach

The differential inequality theory and some novel mathematical analysis techniques are applied.

Findings

A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.

Practical implications

It plays an important role in designing the neural networks.

Originality/value

The obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 11 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 1 July 2000

Gavril Acalugaritei

Acalugaritei networks (ANs) are multidimensional evolutionary hierarchical networks. They are called hierarchical because the sets and subsets of components correspond to…

Abstract

Acalugaritei networks (ANs) are multidimensional evolutionary hierarchical networks. They are called hierarchical because the sets and subsets of components correspond to different ranks (levels), where: the set of “inferior” rank is the subset of rank zero (j = 0) of the set of immediately “superior” rank. The sets and subsets of components will be noted Sij, where: i is the rank number of the set (i = 0,1,2,3); jis the rank number of the subset within the same set (j = 0,1,2, …, n). We will thus distinguish: \curr Sij=(S0jS1jS2jS3j). They are called evolutionary because the most comprehensive set of components is the set of evolutionary relations. They are called multidimensional because the components of the same rank can be classified according to n dimensions (n criteria: ki where: i = 0, 1, 2,…, n). ANs are of different ranks (ANsi, where: i = 0, 1, 2,…,n). In an AN of a certain rank, the set of fundamental components is the set of sequences of ANs of subordinated ranks.

Details

Kybernetes, vol. 29 no. 5/6
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 1 October 2004

Miguel Lloret‐Climent and Jose Luis Bonnet‐Jerez

Describes issues relevant to multilevel systems and, as a particular case, living systems analysed from the entities point of view. As attributes, behaviours, sub‐systems, etc.…

Abstract

Describes issues relevant to multilevel systems and, as a particular case, living systems analysed from the entities point of view. As attributes, behaviours, sub‐systems, etc., entities are primitive terms. For this reason, in examining issues such as the influences between entities, look indirectly at issues referring to different levels in the system. This notion was also extended in considering the environment system and analysing the different relationships between the system and the environment system.

Details

Kybernetes, vol. 33 no. 9/10
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 7 June 2018

Phongsatorn Saisutjarit and Takaya Inamori

The purpose of this paper is to investigate the time optimal trajectory of the multi-tethered robot (MTR) on a large spinning net structures in microgravity environment.

Abstract

Purpose

The purpose of this paper is to investigate the time optimal trajectory of the multi-tethered robot (MTR) on a large spinning net structures in microgravity environment.

Design/methodology/approach

The MTR is a small space robot that uses several tethers attached to the corner-fixed satellites of a spinning net platform. The transition of the MTR from a start point to any arbitrary designated points on the platform surface can be achieved by controlling the tethers’ length and tension simultaneously. Numerical analysis of trajectory optimization problem for the MTR is implemented using the pseudospectral (PS) method.

Findings

The globally time optimal trajectory for MTR on a free-end spinning net platform can be obtained through the PS method.

Research limitations/implications

The analysis in this paper is limited to a planar trajectory and the effects caused by attitude of the MTR will be neglected. To make the problem simple and to see the feasibility in the general case, in this paper, it is assumed there are no any limitations of mechanical hardware constraints such as the velocity limitation of the robot and tether length changing constraint, while only geometrical constraints are considered.

Practical implications

The optimal solution derived from numerical analysis can be used for a path planning, guidance and navigation control. This method can be used for more efficient on-orbit autonomous self-assembly system or extravehicular activities supports which using a tether-controlled robot.

Originality/value

This approach for a locomotion mechanism has the capability to solve problems of conventional crawling type robots on a loose net in microgravity.

Details

Aircraft Engineering and Aerospace Technology, vol. 90 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 1 September 1995

Norio Watanabe and Shusaku Hiraki

Considers a multi‐stage multi‐product production, inventory andtransportation system including lot production processes and develops amathematical model for a pull type ordering…

563

Abstract

Considers a multi‐stage multi‐product production, inventory and transportation system including lot production processes and develops a mathematical model for a pull type ordering system. The decision variables of the presented model are initial ordering quantities and the objective is to minimize the sum of the replenishment level at each inventory point. The model is formulated as an integer programming problem, and an approximate procedure is proposed to obtain a near optimal solution in short time using a mathematical programming package. Finally, shows a numerical example of the model applied to an actual manufacturing system of an automobile parts manufacturer in order to verify the effectiveness of the solution procedure and to clarify the applicability of the modelling approach.

Details

International Journal of Operations & Production Management, vol. 15 no. 9
Type: Research Article
ISSN: 0144-3577

Keywords

Open Access
Article
Publication date: 30 June 2010

Hwa-Joong Kim, Eun-Kyung Yu, Kwang-Tae Kim and Tae-Seung Kim

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the…

Abstract

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the problem with two practical considerations: minimum order size and lost sales. The minimum order size is the minimum amount of items that should be purchased and lost sales involve situations in which sales are lost because items are not on hand or when it becomes more economical to lose the sale rather than making the sale. The objective is to minimize the costs of ordering, item , inventory holding and lost sale over the planning horizon. To solve the problem, we suggest a heuristic algorithm by considering trade-offs between cost factors. Computational experiments on randomly generated test instances show that the algorithm quickly obtains near-optimal solutions.

Details

Journal of International Logistics and Trade, vol. 8 no. 1
Type: Research Article
ISSN: 1738-2122

Keywords

Article
Publication date: 27 March 2024

Yan Zhou and Chuanxu Wang

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to…

Abstract

Purpose

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

Design/methodology/approach

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

Findings

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Originality/value

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 15 March 2024

Lin Sun, Chunxia Yu, Jing Li, Qi Yuan and Shaoqiong Zhao

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued…

Abstract

Purpose

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

Design/methodology/approach

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

Findings

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

Originality/value

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 14 March 2024

Zabih Ghelichi, Monica Gentili and Pitu Mirchandani

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to…

89

Abstract

Purpose

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

Design/methodology/approach

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

Findings

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

Originality/value

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2042-6747

Keywords

Abstract

Details

Recent Developments in Transport Modelling
Type: Book
ISBN: 978-0-08-045119-0

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