Heuristic for the new coordinated dynamic demand lot-size and delivery planning problem

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lin Wang ◽  
Lu Peng ◽  
Rui Liu ◽  
Ligang Cui ◽  
Shan Liu
Keyword(s):  
Optimal Solution ◽  
Planning Problem ◽  
Total System ◽  
Lot Size ◽  
Dynamic Demand ◽  
Setup Cost ◽  
Content Type ◽  
Inventory Costs ◽  
Delivery Planning ◽  
Delivery Policy

Purpose The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP). Design/methodology/approach As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions. Findings Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution. Research limitations/implications To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP. Originality/value Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

scholarly journals Inventory Model with Demand Dependent on Unit Price under Fuzzy Parameters and Decision Variables

2019 ◽  
Vol 8 (3) ◽  
pp. 784-788
Keyword(s):  
Numerical Solutions ◽  
Unit Cost ◽  
Optimal Solution ◽  
Unit Price ◽  
Lot Size ◽  
Setup Cost ◽  
Eoq Model ◽  
Decision Variables ◽  
Holding Cost ◽  
Cost Parameters

An EOQ model with demand dependent on unit price is considered and a new approach of finding optimal demand value is done from the optimal unit cost price after defuzzification. Here the cost parameters like setup cost, holding cost and shortage cost and also the decision variables like unit price, lot size and the maximum inventory are taken under fuzzy environment. Triangular fuzzy numbers are used to fuzzify these input parameters and unknown variables. For the proposed model an optimal solution has been determined using Karush Kuhn-Tucker conditions method. Graded Mean Integration (GMI) method is used for defuzzification. Numerical solutions are obtained and sensitivity analysis is done for the chosen model

scholarly journals Application of the surrogate gradient method for a multi-item single-machine dynamic lot size scheduling problem

2021 ◽  
Vol 3 (7) ◽  
Author(s):  
Minoru Kobayashi
Keyword(s):  
Single Machine ◽  
Gradient Method ◽  
Optimal Solution ◽  
Constraint Equation ◽  
Circuit Board ◽  
Simultaneous Optimization ◽  
Scheduling Problem ◽  
Lot Size ◽  
Setup Cost ◽  
Dynamic Lot Size

AbstractThis study treats a multi-item single-machine dynamic lot size scheduling problem with sequence-independent setup cost and setup time. This problem has various heterogeneous decision features, such as lot sizing and lot sequencing. Traditionally, the problem has been treated by putting artificial constraints on the other feature in order to determine one of them. The proposed model is a Lagrange decomposition and coordination method that aims at simultaneous optimization of these decision features; however, smooth convergence to a feasible near-optimal solution has been a problem. So, in this paper, we propose a model that improves the constraint equation of the existing model and showed that it satisfies the Karush–Kuhn–Tucker (KKT) condition when we obtained a feasible solution. In addition, by applying the surrogate gradient method, which has never been applied to this problem before, it was shown that smoother convergence than before can be achieved through actual example of printed circuit board.

A distributed and integrated method for cooperative mission planning of multiple heterogeneous UAVs

2018 ◽  
Vol 90 (9) ◽  
pp. 1403-1412
Author(s):  
Weinan WU ◽  
Naigang Cui
Keyword(s):  
Degrees Of Freedom ◽  
Planning Process ◽  
Feasible Solution ◽  
Optimal Solution ◽  
Path Following ◽  
Mission Planning ◽  
Planning Problem ◽  
Content Type ◽  
Integrated Method ◽  
Operating Rate

Purpose The purpose of this paper is to develop a distributed and integrated method to get a fast and feasible solution for cooperative mission planning of multiple heterogeneous unmanned aerial vehicles (UAVs). Design/methodology/approach In this study, the planning process is conducted in a distributed framework; the cooperative mission planning problem is reformulated with some specific constraints in the real mission; a distributed genetic algorithm is the algorithm proposed for searching for the optimal solution; genes of the chromosome are modified to adapt to the heterogeneous characteristic of UAVs; a fixed-wing UAV’s six degrees-of-freedom (DOF) model with a path following method is used to test the proposed mission planning method. Findings This method not only has the ability to obtain good feasible solutions but also improves the operating rate vastly. Research limitations/implications This study is only applied to the case where the communication among UAVs is linked during the mission. Practical implications This study is expected to be practical for a real mission because of its fast operating rate and good feasible solution. Originality/value This solution is tested on a fixed-wing UAV’s 6-DOF model by a path following method, so it is believable from the perspective of an autonomous UAV guidance and control system.

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

Trajectory tracking and point stability of three-axis aero-dynamic pendulum with MPC strategy in disturbance environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Liu ◽  
Jiahong Xu ◽  
Yuhong Liu
Keyword(s):  
Predictive Model ◽  
Trajectory Tracking ◽  
Control Strategy ◽  
Kinematic Model ◽  
Control Variable ◽  
Optimal Solution ◽  
Intelligent Manufacturing ◽  
Pendulum System ◽  
Content Type ◽  
3D Space

Purpose The purpose of this research on the control of three-axis aero-dynamic pendulum with disturbance is to facilitate the applications of equipment with similar pendulum structure in intelligent manufacturing and robot. Design/methodology/approach The controller proposed in this paper is mainly implemented in the following ways. First, the kinematic model of the three-axis aero-dynamic pendulum is derived in state space form to construct the predictive model. Then, according to the predictive model and objective function, the control problem can be expressed a quadratic programming (QP) problem. The optimal solution of the QP problem at each sampling time is the value of control variable. Findings The trajectory tracking and point stability tests performed on the 3D space with different disturbances are validated and the results show the effectiveness of the proposed control strategy. Originality/value This paper proposes a nonlinear unstable three-axis aero-dynamic pendulum with less power devices. Meanwhile, the trajectory tracking and point stability problem of the pendulum system is investigated with the model predictive control strategy.

Less-skilled pilot decision support

2019 ◽  
Vol 91 (5) ◽  
pp. 790-802
Author(s):  
Jozsef Rohacs ◽  
Istvan Jankovics ◽  
Daniel Rohacs
Keyword(s):  
Control System ◽  
Decision Support ◽  
Total System ◽  
Workload Management ◽  
Content Type ◽  
Subjective Analysis ◽  
Supporting System ◽  
Safety Aspects ◽  
Concept Validation ◽  
Small Aircraft

PurposeThe purpose of this paper is to overview the systems and their elements developing for supporting the less-skilled pi-lots.Design/methodology/approachSeveral European (like EPATS, SAT-Rdmp, Pplane, Esposa, Clean Sky2) and national projects (NASA SATS, Hungarian SafeFly) develop the personal/small aircraft and personal/small aircraft transportation systems. The projects had analysed the safety aspects, too, and they underlined the aircraft will be controlled by so-called less-skilled pilots (owners, renters), having less experiences. The paper defines the cross-connected controls, introduces the methods of subjective analysis in pilot decision processes, improves the pilot workload model, defines the possible workload management and describes the developing pilot decision support system.FindingsAnalysing the personal/small aircraft safety aspects, a unique and important safety problem induced by less-skilled pilots has been identified. The considerable simplification of the air-craft control system, supporting the pilot subjective decisions and introducing the pilot work-load management, may eliminate this problem.Research limitations/implicationsOnly the system elements have been used in concept validation tests.Practical implicationsThe developing pilot supporting system in its general form has on - board and ground sub-systems, too, except a series of elements integrated into the pilot cockpit environment and control system. Several system elements (sensors, integrated controls, etc.) might be implement now, but the total system need further studies. The subjective decision process needs further development of the methodology and concept validation.Social implicationsThe system may catalyse the society acceptance of the personal aircraft and their safer piloting, applicability.Originality/valueThe paper introduces an original supporting system for less-skilled pilots.

scholarly journals An inland-depots-for-empty-containers-model for the hinterland

2017 ◽  
Vol 2 (2) ◽  
pp. 126-141 ◽  
Author(s):  
Stephanie Finke ◽  
Herbert Kotzab
Keyword(s):  
Linear Optimization ◽  
Point Of View ◽  
Mixed Integer ◽  
Total System ◽  
Empty Container ◽  
Content Type ◽  
Shipping Company ◽  
Linear Optimization Model ◽  
Mixed Integer Linear Optimization ◽  
Empty Containers

Purpose The purpose of this paper is to figure out in which way a hinterland-based inland depot model can help a shipping company in solving the empty container problem at a regional level. The repositioning of empty containers is a very expensive operation that does not generate profits. Consequently, it is very important to provide an efficient empty container management. Design/methodology/approach In this paper, the empty container problem is discussed at a regional repositioning level. For solving this problem, a mixed-integer linear optimization model is developed and validated by using the German hinterland as a case. Findings The findings show that the hinterland-based solution is able to reduce the total system costs by 40 per cent. In addition, total of truck kilometres could be reduced by more than 30 per cent too. Research limitations/implications This research is based on German data only. Originality/value This paper closes the gap in empty container repositioning research by looking at the hinterland dimension from a single shipping company point of view.

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