Van-Dat Cung

Optimal configuration of assembly supply chains using analytical target cascading

This paper proposes to apply analytical target cascading (ATC) for configuring assembly supply chains with convergent structures. Individual enterprises in a supply chain are represented as separate elements in an ATC hierarchy. They are able to maintain autonomous and heterogeneous decision systems for optimising their private decision variables and objectives. They collaborate vertically and laterally along the ATC hierarchy through their common decisions to achieve the overall consistency and optimality. ATC offers a competitive balance between computational efficiency and effectiveness while providing an opportunity for parallel computation to further improve the efficiency. This paper also investigates the feasibility for individual enterprises to set local targets while participating in the supply chain configuration (SCC). SCC usually involves discrete decision variables, causing significant difficulties for existing ATC techniques to achieve system consistency. Therefore, a new consistency scheme has to be proposed in this paper, including two techniques: importance weighting factor (IWF) and dynamic constraints (DC). A case study is used to demonstrate the application of the ATC method for solving typical SCC problems. A series of comparative analyses are conducted to identify the strengths of the ATC method and demonstrate the effectiveness of the proposed consistency scheme.

Decentralised planning coordination with quantity discount contract in a divergent supply chain

This paper proposes to solve a supply chain planning problem with realistic features. The problem consists of planning productions, transportations and storage activities in a supply chain at a tactical level on a finite horizon. The main features considered are decentralised decision making and iteration of the planning process on a rolling horizon basis. In each planning process, the actors optimise their local planning and coordinate to achieve a good overall planning. A multi-agent system is used to model such supply chain behaviour. The study is conducted in a divergent two-echelon supply chain with one manufacturer and multiple independent retailers. Coordination is achieved using a standard contract in practice, known as the ‘quantity discount’ contract. The planning framework on the supply chain structure is detailed. Lot-sizing models integrating the quantity discount are presented for the local planning problems. Experimental tests are conducted with three major parameters: quantity discount price, quantity discount breakpoint and rolling horizon length. They are used to determine the quantity discount parameters in achieving the best supply chain profit, and to analyse the increasing profit of the actors. A decision-making tool which is able to consider realistic features of supply chain planning is therefore resulted.

An efficient two-phase iterative heuristic for Collection-Disassembly problem

Abstract Closing the loop in the supply chains is one of the mandatory conditions for more sustainable development. The Collection-Disassembly Problem appears in the reverse part of the closed-loop supply chains. Its aim is to coordinate the activities of collection of end-of-life products from collection centres and their subsequent disassembly. The disassembly step is required for efficient remanufacturing and recycling of returned products. The Collection-Disassembly problem integrates such optimization problems as dynamic lot-sizing and vehicle routing in general cases. In this paper, we develop a Two-Phase Iterative Heuristic to efficiently address large size instances. The numerical tests show that the heuristic provides good solutions under acceptable computational time.

Two classical transportation problems revisited: Pure constant fixed charges and the paradox

We analyze degeneracy characterizations for two classical problems: the transportation paradox in linear transportation problems and the pure constant fixed charge transportation problem. Solving the pure constant fixed charge problem is equivalent to finding a basic tree solution with maximum degree of degeneracy. Problems possess degenerate solutions if the equal subsum property is satisfied for the supplies and demands. Determining the existence of degeneracy is an NP-complete problem. But this NP-hardness remains even if all equal subsums are known in advance. For the second problem, the transportation paradox, there exists a vast literature that typically describes methods, derived within the framework of the classical transportation algorithm, for determining solutions where the more-for-less phenomenon occurs. We show how to solve this problem as a simple standard network flow problem. The paradox is linked to overshipment solutions, which belong to supply and demand configurations that tend to have a high degree of degeneracy.

Integrated Procurement-Disassembly Problem

This paper proposes a novel problem called integrated pro- curement–disassembly problem. The problem combines vehicle routing problem and disassembly line balancing problem for collecting and dis- assembling End-of-Life (EOL) products, respectively. The integration of those problems is motivated by the necessity to reduce total cost in reverse supply chain context. After collecting the EOL products from suppliers, the disassembly process begins to release the demanded parts. The objective function aims to minimize the total cost consisting product collection and opening disassembly workstations. The constraints consider vehicle routing problem to supply the disassembly line with EOL products, disassembly line and balancing inventory coordinating those problems. The decision variables include trips sequences associated to collect the products, disassembly task assignment into workstations, and the inventory level.

Optimal repositioning and purchasing policies in returnable container management

This work focuses on the optimization of the returnable container management problem in a global and sustainable supply chain context. The problem consists in: (1) choosing the best way to reposition empty containers between several sites for next rounds of use and (2) purchasing the right quantity of new containers at the right period to meet system requirements for product transportation. For this problem a linear integer program model is proposed. Based on some partial network flow properties (section IV.C), a decomposition into two independent models, purchasing and transportation, has been developed to determine an optimal policy. The benefits of this decomposition, on the technical and industrial level, will be presented and discussed.

Optimal scheduling for coordination renewable energy and electric vehicles consumption

The massive penetration of electric vehicles may lead to strong grid impacts, especially on the distribution grid. The Solar Mobility concept aims to resolve this situation using photovoltaic systems for recharging the vehicles. Key element for solar mobility is the energy management system, which minimizes the grid impact and maximizes the solar coverage during charging process. This paper presents the practical experience achieved with the operation of ten electrified vehicles and solar station during two years. The optimal load scheduling problem of electric vehicles will be presented. It is shown how the Energy Management System provides significant improvement of solar coverage and grid impact thought the demonstration period.

Decentralised capacitated planning with minimal-information sharing in a 2-echelon supply chain

This paper aims at modelling decentralised planning at the tactical level, with minimal-information sharing coordination, in a 2-echelon supply chain with multiple actors at each echelon. Suppliers manage production and storage at the upstream echelon, while retailers manage transportation and storage at the downstream echelon. The main features of the planning process are (1) decentralisation and coordination using contracts and sharing of only order/supply proposals, and (2) iteration on a rolling horizon. Actor planning is modelled as a capacitated lot-sizing problem on a finite horizon, with the focus on quality of service. The objective is to minimise costs, with a high lost sales penalty if demand is not met. Two other decision problems are pointed out and modelled with Mixed Integer Programming: (1) lost sales allocation between the retailers when their demands cannot be satisfied; and (2) allocation of orders between the suppliers. A multi-agent system combines simulation of the planning process and optimisation of the local decision processes. Several strategies, including retailers’ beliefs about suppliers’ production capacity are proposed and experimentally tested, with two patterns of production capacities. The results compare the proposed allocation strategies and highlight the relevance of the proposed framework for the studied planning problem.

Service network design in short and local fresh food supply chain

This paper aims at developing efficient solving methods for an original service network design problem imbued with sustainable issues. Indeed the network has to be designed for short and local supply chain and for fresh food products. The original features of the problem are the seasonality of supply, the limitation of transshipments for a product and no possibility of storage between consecutive periods. Decisions at strategic and tactical level are (1) decisions on a subset of hubs to open among a given set of potential locations, (2) transportation services to open between the actors and (3) flow quantities for the fresh food products. We propose for this problem a Mixed Integer Programming formulation and two solving techniques: Benders Decomposition and Dynamic Slope Scaling Procedure. These techniques are adapted to the problem and some experimental tests are conducted in order to compare the approaches on large-scale instances.

Sample average approximation for multi-vehicle collection–disassembly problem under uncertainty

The implementation of the circular economy is increasingly supported by many governments. It is performed by integrating the activities of reverse supply chain (RSC) into those of forward supply chain. However, many companies that traditionally focus on the activities of forward supply chain have decided to collaborate with third-party reverse logistics providers to manage the RSC. This collaboration motivates the work presented in this paper to propose better decisions for decision makers in the providers under the fact that integrating decisions of the collection of End-of-Life products and their disassembly process proposes a RSC with better performance. In this paper, an integrated problem concerning those decisions is presented and formalised. It also deals with the uncertainty of the quality and the quantity of products as well as the demands of the associated components. Two approximate methods are developed to provide the solutions.