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Purpose: Nowadays, the sustainability awareness is challenging the concept of growth that has guided economic activity for decades. Deep restructuring of supply chains is mandatory to go further concerning the environmental balance (e.g., energy alternatives, carbon footprint, and greenhouse gas, GHG) and to place it in the top priorities of companies’ agenda. Apart from the environmental and social concerns, the economic counterpart strongly impacts the enterprise’s practices and supply chain decisions. Besides, industrial supply chains are characterized by complex partnershipnetworks that introduce great challenges to the paradigm of fully integration and efficiency. Competitiveness and risk exposure increase substantially in realbusiness environment and, therefore, the assurance of service levels to global customers results progressively more complex for supply chain managers and practitioners. Methodology: Following the previous motivations, a novel framework was developed to help the decision-making process and to support operational decisions within a risk environment that trades between supply chain environmental goal, service level to customer, energy targets and economic criteria. The proposed contribution develops an optimization approach to help ISC managers at the planning decisionlevel while accounting for the sustainability concern and to the commitment to customers. The mathematical formulation relies on a discrete time approach and an optimization model (MILP formulation) is implemented to optimally manageindustrial performance criteria. Sustainability conditions, at the economic (e.g., operating costs, due dates penalties) and at the environmental (e.g., energy, carbon footprint or GHG) levels are attained. The optimization model is used to enhance efficiency goal for the SC planning decisions. The former is defined as the optimal value that ensure efficiency results, while fulfilling environmental metrics and target values. Results: The model applicability is shown through the solution of an industrial example, and the impact of sustainable policies in the SC planning strategy is evaluated. Several managing settings are analyzed, in order to account for different balances of the performance criteria defining the model objective. As a major finding it is important to notice that environmental indicators are those emphasizing the implementation success, while the economic dimension ranks the efficiency reached. The results showed that important improvements can be obtained for a sustainable print, while keeping competitiveness and customer service metrics. These bring new insides concerning the studied operational characteristics. So, as a final statement, a novel approach was developed to help the decision- making process at the SC planning level. The industrial example showed the model applicability, and the achieved results illustrate the challenges placed by the integrated sustainability criteria, environmental requirements, and economic performances. Research limitations: Further model improvements are being developed to tackle other performance dimensions, that are mutual related, but emphasize different performance’s requirements. Originality: The proposal is under development and some working on is being performed. The industrial application is being improved and future sustainability conditions and scenarios are also under evaluation. [ABSTRACT FROM AUTHOR]

Purpose: Nowadays, the sustainability awareness is challenging the concept of growth that has guided economic activity for decades. Deep restructuring of supply chains is mandatory to go further concerning the environmental balance (e.g., energy alternatives, carbon footprint, and greenhouse gas, GHG) and to place it in the top priorities of companies’ agenda. Apart from the environmental and social concerns, the economic counterpart strongly impacts the enterprise’s practices and supply chain decisions. Besides, industrial supply chains are characterized by complex partnership networks that introduce great challenges to the paradigm of fully integration and efficiency. Competitiveness and risk exposure increase substantially in real business environment and, therefore, the assurance of service levels to global customers results progressively more complex for supply chain managers and practitioners. Methodology: Following the previous motivations, a novel framework was developed to help the decision-making process and to support operational decisions within a risk environment that trades between supply chain environmental goal, service level to customer, energy targets and economic criteria. The proposed contribution develops an optimization approach to help ISC managers at the planning decision level while accounting for the sustainability concern and to the commitment to customers. The mathematical formulation relies on a discrete time approach and an optimization model (MILP formulation) is implemented to optimally manage industrial performance criteria. Sustainability conditions, at the economic (e.g., operating costs, due dates penalties) and at the environmental (e.g., energy, carbon footprint or GHG) levels are attained. The optimization model is used to enhance efficiency goal for the SC planning decisions. The former is defined as the optimal value that ensure efficiency results, while fulfilling environmental metrics and target values. Results: The model applicability is shown through the solution of an industrial example, and the impact of sustainable policies in the SC planning strategy is evaluated. Several managing settings are analyzed, in order to account for different balances of the performance criteria defining the model objective. As a major finding it is important to notice that environmental indicators are those emphasizing the implementation success, while the economic dimension ranks the efficiency reached. The results showed that important improvements can be obtained for a sustainable print, while keeping competitiveness and customer service metrics. These bring new insides concerning the studied operational characteristics. So, as a final statement, a novel approach was developed to help the decision-making process at the SC planning level. The industrial example showed the model applicability, and the achieved results illustrate the challenges placed by the integrated sustainability criteria, environmental requirements, and economic performances. Research limitations: Further model improvements are being developed to tackle other performance dimensions, that are mutual related, but emphasize different performance’s requirements. Originality: The proposal is under development and some working on is being performed. The industrial application is being improved and future sustainability conditions and scenarios are also under evaluation. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage model for optimal planning and operation of a distribution network. Optimal siting and sizing of renewable energy sources (RES) as well as electrical energy storage (EES) systems are considered in the proposed hybrid energy system. In this context, the planning problem is considered as a master problem, while there are different sub-problems associated with the short-term operational problem. To properly handle the uncertainties of forecasted load as well as renewable power generations, fair stochastic models are involved in the sub-problems based on historical data of a real grid. The objective function of this problem consists of total investment cost and total operating costs of installed assets. The proposed scheme is implemented on a distribution test system and the obtained results demonstrate the applicability and efficiency of this model in dealing with the optimal operation and planning of distribution networks in the presence of a large number of decision variables. Moreover, simulation results show that joint utilization of the EESs and RESs reduces the annual operational cost and can handle the fluctuations of RESs power generations and hourly demanded loads. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) planning problem, i.e. finding the optimal size and location of DG units, is a Mixed Integer Non-linear Problem (MINLP). Typically finding the optimal solution of a MINLP problem is a complicated duty. This paper is focused on optimal solution of DG planning problem (DGPP) using Imperialist Competitive Algorithm (ICA) in distribution networks. DGPP is converted to an optimization problem with the multi-objective function including the minimum network power losses, the better voltage regulation and the improving voltage stability of the distribution system. The effectiveness of the proposed approach is confirmed on 33-bus and 69-bus test systems under different operating conditions. The comparative analysis is made between other evolutionary methods like GA and PSO through some performance indices to demonstrate its flexibility and effectiveness. [ABSTRACT FROM PUBLISHER]

The development of electric vehicles cannot be separated from charging infrastructures. At present, the construction of electric vehicle charging stations faces the problems on siting and sizing. This paper introduces the optimization process of the sizing and siting of electric vehicle charging stations, defines variables to represent the charging demand; abstracts the structure of road network to model and simulate with graph theory; solves the problem with Cplex. The objective of the model is to minimize the integrated cost of charging stations and consumers. The calculation results, using the data of Stockholm, Sweden, show that the method can effectively reduce the construction and operation costs, and facilitate user charging. [ABSTRACT FROM PUBLISHER]

The multi-propeller multifunction aerial robot with two manipulators has the potential to deal with arm-operating in the air. However, the interaction between the main-body and manipulator subsystems make the robot be difficult to accomplish the task of arm-operating. This paper investigates the modeling, planning, and control problem of the robot for arm-operating purposes. The paper presents the dynamic analysis of the aerial robot not contacting with the environment. The dynamics of the whole system are partitioned into several meaningful parts: the main-body dynamics, the manipulator dynamics, and the interaction dynamics. Furthermore, an optimal planning strategy which can minimize the interaction between main-body subsystem and manipulator subsystem is proposed. The paper also investigates a simple composite controller that is composed of main-body controller and manipulator controller. Each subcontroller is designed based on the partitioned dynamics. The simulation results validate the dynamic model, the benefit of the optimal planning approach, and the effectiveness of the composite controller. [ABSTRACT FROM PUBLISHER]

To meet the demand of crops irrigation water, the optimal planning model of the field water saving irrigation, in which minimum incremental annual cost of field water saving irrigation engineering is the objective function, has been established based on types of water resource, agricultural utilizable water yield, crop planting structure, status of water saving irrigation and feasibility of each water saving irrigation technology. To use the model, the Xinjiang Hetian region optimal plan of water saving irrigation that includes optimal development scale of water saving irrigation for each crop in the region has been put forward in 2020. The model provides a scientific basis for reasonable planning of water saving irrigation and optimal allocation of water and land resources in region. [ABSTRACT FROM PUBLISHER]