Hwa-Joong Kim

Disassembly scheduling: literature review and future research directions

Disassembly scheduling, one of the important operational problems in disassembly systems, can be generally defined as the problem of determining the quantity and timing of the end-of-use/life products while satisfying the demand of their parts over a planning horizon. This paper presents a literature review on this planning problem in disassembly systems. First, the basic form of the problem is defined with a mathematical formulation. To characterize the differences between assembly and disassembly processes, the effects of the divergence property are also explained with respect to the zero inventory property, indispensable surplus inventory, and mathematical representation. Then, we review the existing research articles on the basic problem and its generalizations. A systematic scheme for classifying problems is also suggested. Finally, we suggest several future research directions.

Disassembly Scheduling with Multiple Product Types

Abstract We consider the problem of determining the disassembly schedules of used products while satisfying the demand of their parts/components over a planning horizon. The case of multiple product types with parts commonality is considered for the objective of minimizing the sum of setup, disassembly operation, and inventory holding costs. A heuristic algorithm is proposed using the linear programming relaxation approach. Test results of the case study on the data obtained from a disassembly shop show that the heuristic algorithm suggested in this paper works well for practical problems.

Two-phase heuristic for disassembly scheduling with multiple product types and parts commonality

Disassembly scheduling is one of the important planning problems in disassembly systems, and generally defined as the problem of determining the quantity and timing of disassembling products in order to satisfy the demand of their parts or components over a planning horizon. This paper focuses on the case of multiple product types with parts commonality for the objective of minimizing the sum of set-up, disassembly operation and inventory-holding costs, and it suggests a two-phase heuristic in which an initial solution is obtained using a linear-programming relaxation, and then improved by perturbing the initial solution using a dynamic programming algorithm with look-ahead check. Computational experiments are done on a number of randomly generated test problems and the results show that the heuristic suggested in this paper can give near-optimal solutions within a short computation time.

A branch and bound algorithm for disassembly scheduling with assembly product structure

This paper considers a production planning problem in disassembly systems, which is the problem of determining the quantity and timing of disassembling end-of-use/life products in order to satisfy the demand of their parts or components over a planning horizon. The case of single product type without parts commonality is considered for the objective of minimizing the sum of setup and inventory holding costs. To show the complexity of the problem, we prove that the problem is NP-hard. Then, after deriving the properties of optimal solutions, a branch and bound algorithm is suggested that incorporates the Lagrangean relaxation-based upper and lower bounds. Computational experiments are performed on a number of randomly generated problems and the test results indicate that the branch and bound algorithm can give optimal solutions up to moderate-sized problems in a reasonable computation time. A Lagrangean heuristic for a viable alternative for large-sized problems is also suggested and compared with the existing heuristics to show its effectiveness.

A Lagrangean heuristic algorithm for disassembly scheduling with capacity constraints

This paper considers the problem of determining the disassembly schedule (quantity and timing) of products in order to satisfy the demand of their parts or components over a finite planning horizon. The objective is to minimize the sum of set-up, disassembly operation, and inventory holding costs. As an extension of the uncapacitated versions of the problem, we consider the resource capacity restrictions over the planning horizon. An integer program is suggested to describe the problem mathematically, and to solve the problem, a heuristic is developed using a Lagrangean relaxation technique together with a method to find a good feasible solution while considering the trade-offs among different costs. The effectiveness of the algorithm is tested on a number of randomly generated problems and the test results show that the heuristic suggested in this paper can give near optimal solutions within a short amount of computation time.

Capacitated disassembly scheduling with random demand

This paper considers disassembly scheduling, which is the problem of determining the quantity and timing of the end-of-use/life products to be disassembled while satisfying the demand for their parts obtained from disassembling the products over a planning horizon. This paper focuses on the problem with stochastic demand of parts/modules, capacity restrictions on disassembly resources, and multiple product types with a two-level product structure. The two-level product structure implies that an end-of-use/life product is hierarchically decomposed into two levels where the first level corresponds to the parts/modules and the second level corresponds to the product. We formulate the problem as a stochastic inventory model and to solve the problem we propose a Lagrangian heuristic algorithm as well as an optimisation algorithm for the sub-problems obtained from Lagrangian decomposition. The test results on randomly generated problems show that the Lagrangian heuristic algorithm demonstrates good performance in terms of solution quality and time.

Disassembly scheduling with capacity constraints: minimizing the number of products disassembled

Abstract Disassembly scheduling, one of the important operational problems in disassembly systems, is the problem of determining the timing and quantity of disassembling used or end-of-life products to satisfy the demand of their parts or components over a given planning horizon. This paper focuses on the case of single product type without parts commonality while the resource capacity restrictions are considered explicitly. The problem is formulated as an integer programming model with the objective of minimizing the number of products disassembled, and a solution algorithm is suggested after deriving its optimal solution properties. Computational experiments are done on various test problems, and the results show that the algorithm suggested in this paper gives optimal solutions for the test problems within a very short amount of computation time.

Scheduling for an arc-welding robot considering heat-caused distortion

This paper focuses on an arc-welding robot scheduling problem, which is the problem of determining the sequence of welding operations while avoiding heat-caused distortion for the objective of minimizing the time required to complete a given set of welding operations. Each welding operation is specified by a weld line with two end points, each of which can be a possible starting point of the welding operation for that weld line. Because of the heat-caused distortion, there must be a certain period of time (delay) between welding operations associated with weld lines near each other. We develop several heuristic algorithms, in which heuristics for the travelling salesman problem are modified to cope with characteristics of the problem considered here. To show the performance of the heuristics suggested in this paper, computational experiments are performed on a number of randomly generated test problems and results are reported.

A Lagrangian Heuristic for Determining the Speed and Bunkering Port of a Ship

This study addresses the problem of determining the ship speed and bunkering ports in a ship route. All of the previous research has investigated the ship speed optimization issues by assuming that the ship navigates at constant speed or by ignoring the bunkering port decision. In this study, the problem of determining the variable speed and bunkering port is formulated mathematically with a nonlinear program in order to minimize the bunker fuel, ship time costs, and carbon tax imposed on greenhouse gas emissions. This study then provides a Lagrangian heuristic by deriving a property for a relaxed problem. The performance of the heuristic is evaluated and analysed using the data obtained from the literature, real practice and random generation.

Optimizing ship speed to minimize fuel consumption

Abstract Owing to high fuel costs and environmental regulations, the optimization of ship speed to minimize fuel consumption and reduce carbon emissions has become a hot issue in the maritime industry. In this paper, we study the sailing speed optimization problem for a ship operating on a route having a specified sequence of calling ports with time windows for calling time. The considered problem can be formulated as a non-linear program. We derive the intrinsic properties of the problem and develop an optimal algorithm based on the properties. Computational experiments show that the developed algorithm in this paper is efficient in finding an optimal solution.