• Journal of Distribution Science
• /
• v.10 no.12
• /
• pp.19-24
• /
• 2012

Purpose - This paper discusses the heterogeneous fixed fleet vehicle routing problem with pick-up and delivery (HFFVRPPD), for vehicles with different capacities, fixed costs, and travel costs. Research Design, data, methodology - This paper made nine assumptions for establishing a mathematical model to describe HFFVRPPD. It established a practical mathematical model, and because of the non-deterministic polynomial-time hard (NP-hard), improved the traditional simulated annealing algorithm and tested a new algorithm using a certain scale model. Result - We calculated the minimum cost of the heterogeneous fixed fleet vehicle routing problem (HFFVRP) with a single task and, on comparing the results with the actual HFFVRP for the single task alone, observed that the total cost of HFFVRPPD reduced significantly by 46.7%. The results showed that the new algorithm provides better solutions and stability. Conclusions - This paper, by comparing the HFFVRP and HFFVRPPD results, highlights certain advantages of using HFFVRPPD in physical distribution enterprises, such as saving distribution vehicles, reducing logistics cost, and raising economic benefits.

• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1117-1119
• /
• 1999

This paper presents a new approach for the optimal routing problem of distribution system planning using the well known Hopfield Neural Network(HNN) method. The optimal routing problem(ORP) in distribution system planning(DSP) is generally formulated as combinational mixed integer problem with various equality and inequality constraints. For the exceeding nonlinear characteristics of the ORP most of the conventional mathematical methods often lead to a local minimum. In this paper, a new approach was made using the HNN method for the ORP to overcome those disadvantages. And for this approach, a appropriately designed energy function suited for the ORP was proposed. The proposed algorithm has been evaluated through the sample distribution planning problem and the simulation results are presented.

• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1123-1125
• /
• 1999

This paper proposes an optimization technique using Genetic Algorithm(GA) for service restoration in the distribution system. Restoration planning problem can be treated as a combinatorial optimization problem. So GA is appropriate to solve the service restoration problem in the distribution network. But searching capabilities of the GA can be enhanced by developing relevant repairing operation and modifying GA operations. In this paper, we aimed at finding appropriate open sectionalizing switch position for the restoration of distribution networks after disturbances using enhanced GA with repairing operation and modified mutation. Simulation results show that proposed method found the open sectionalizing switches with less out of service area and minimize transmission line losses and voltage drop.

• Journal of Information Processing Systems
• /
• v.18 no.5
• /
• pp.665-676
• /
• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2008.10a
• /
• pp.267-284
• /
• 2008

Consider a supply chain where products are produced at a manufacturing system, shipped to a distribution center, and then supplied to customers. The distribution center controls inventory based on a base-stock policy, and whenever a unit of product is demanded by a customer, an order is released to the production system. Unsatisfied demand is backordered, and the inventory and backordered units are a function of the base-stock level. The manufacturing system is modeled as an M/M/s/c queueing system, and orders exceeding the limited buffer capacity are blocked and lost. The throughput of the manufacturing system and the steady state distribution of the outstanding orders are functions of number of servers and buffers of the manufacturing system. There is a profit obtained from throughput and costs due to servers and buffers of the manufacturing system, and also costs due to inventory positions of the distribution center, and we want to maximize the total production profit minus the total cost of the supply chain by simultaneously determining the optimal number of servers and buffers of the manufacturing system and the optimal base-stock level of the distribution center. We develope two algorithms, one analytical but without guarantee of the optimal solution and one optimal but without complete analytical proofs. The problem integrates strategic problem of the manufacturing system with tactical problem of the distribution center in a supply chain.

• Journal of the Korea Society of Computer and Information
• /
• v.6 no.4
• /
• pp.163-167
• /
• 2001

Many of these studies represent a large scale distribution network with a unified formulation by using defined symbols. This can be evaluated as a valuable progress toward accomplishing of a systematic approach the area of distribution network. Unfortunately. transportation problem and inventory policy applied in these studies have an assumption of using an unique supplier for calculating the transportation cost among each distribution echelon. This assumption can cause many problems such that transportation problem is assumed as linear problem, too many number of distribution center are allowed to operate and many more. In order to overcome above unrealistic problems, we developed an algorithm of responding to customers' demand under the refill allowance of same level supply as anew constructional method of inventory distribution network. When backorders are happened in regional distribution center, this algorithm allows transferring finished goods to customer directly from vicinal Regional distribution center instead of existing central distribution center for quick response.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.580-582
• /
• 2005

This paper presents a new method which applies a genetic algorithm(GA) for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. The distribution system loss minimization re-configuration problem is in essence a 0-1 planning problem which means that for typical system scales the number of combinations requiring searches becomes extremely large. In order to deal with this problem, a new a roach which applies a GA was presented. Briefly, GA are a type of random number search method, however, they incorporate a multi-point search feature. Further, every point is not is not separately and respectively renewed, therefore, if parallel processing is applied, we can expect a fast solution algorithm to result.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.36 no.4
• /
• pp.231-239
• /
• 1987

Distribution system is one of large and complicated sytem, consisted of a great number of components. Therefore efficient operation based on precise analysis and computation methods is indispensable accommodating growing loads. This paper describes an optimal operation problem to relieve overload flow in radial distribution systems by using modified block model. The problem is formulated as a network problem of synthesizing the optimal spanning tree in a graph, branch and bound method is used for the optimization. Especially modified block model proposed in this paper is validated more practical than conventional model. These methods can be applied to two types of distribution system problems such as, 1) planning problem to check the capability of relieving overload at normal rating, 2) emergency operation problem to determine switching scheme for minimizing customer loads affected by a fault. Examples of application to these problems are discussed.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.4
• /
• pp.1386-1396
• /
• 2017

In this paper, a new approach is proposed to select the optimal sitting and sizing of distributed solar photovoltaic generation (SPVG) in a radial electrical distribution systems (EDS) considering load/generation uncertainties. Here, distributed generations (DGs) allocation problem is modeled as optimization problem with network loss based objective function under various equality and inequality constrains in an uncertain environment. A boundary power flow is utilized to address the uncertainties in load/generation forecasts. This approach facilitates the consideration of random uncertainties in forecast having no statistical history. Uncertain solar irradiance is modeled by beta distribution function (BDF). The resulted optimization problem is solved by a new Dynamic Harmony Search Algorithm (DHSA). Dynamic band width (DBW) based DHSA is proposed to enhance the search space and dynamically adjust the exploitation near the optimal solution. Proposed approach is demonstrated for two standard IEEE radial distribution systems under different scenarios.

• Journal of Distribution Science
• /
• v.15 no.2
• /
• pp.15-20
• /
• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.