Economic Lot Scheduling for Two-Product Problem

In this paper we propose an algorithm for the two-product single machine Economic Lot Scheduling Problem (ELSP). Past research on this problem has relied heavily on the assumption that both products are produced cyclically. In particular Boctor's algorithm provides optimal solution to the two-product problem under such assumption. We first simplify Boctor's algorithm and then propose an algorithm which allows for the unequal cycle time for the more frequently manufactured product. We show that the cost corresponding to our solution is either less than 1.015 times the cost obtained from the Independent Solution, which is a lower bound of the optimal solution, or is better than that obtained by Boctor's algorithm. An example is used to show that the difference in cost can be as much as 24%.     

Parallel simulation algorithm for maintenance optimization based on directed Acyclic Graph

An efficient simulation algorithm for the quantification of reliability performance indicators of a complex system is demonstrated in the paper that is based on Monte Carlo method. A directed Acyclic Graph is used as a useful system representation. A parallel simulation technique is used in the algorithm which is based on the construction of the special course of life sequence of transformed transition times subjected to the corresponding part of the Acyclic Graph. The parts of the Acyclic Graph represent individual subsystems of a given system and may be effectively evaluated from the reliability point of view. The wide range of models for both deterministic and stochastic processes applied on the terminal nodes of the Acyclic Graph is allowed in the algorithm. The use of the algorithm for comparative theoretical calculations as well as for industrial applications is shown by a visual demonstration. A cost-optimization problem is shortly introduced which may be fully solved by the algorithm using additional genetic algorithms as an applicable optimization technique. The problem takes into account also additional objective that is defined as a prescribed constraint of a selected reliability performance indicator. The solution of the cost-optimization problem is demonstrated on two practical examples.     

Cause and effect analysis by fuzzy relational equations and a genetic algorithm

This paper proposes using a genetic algorithm as a tool to solve the fault diagnosis problem. The fault diagnosis problem is based on a cause and effect analysis which is formally described by fuzzy relations. Fuzzy relations are formed on the basis of expert assessments. Application of expert fuzzy relations to restore and identify the causes through the observed effects requires the solution to a system of fuzzy relational equations. In this study this search for a solution amounts to solving a corresponding optimization problem. An optimization algorithm is based on the application of genetic operations of crossover, mutation and selection. The genetic algorithm suggested here represents an application in expert systems of fault diagnosis and quality control.     

Job shop scheduling with alternative machines

In this paper we investigate the problem of minimizing the mean flow time in a general job shop type machining system with alternative machine tool routeings. An analytical formulation of the problem as a mixed integer programming is developed. An efficient algorithm based on this formulation is developed to solve the problem by decomposing it into subproblems that are easier to solve. The algorithm solves large problems in relatively short time. A second algorithm based on the SPT rule is developed and its performance is compared with the first algorithm. A greedy procedure is also developed for the case when a penalty cost is associated with adding alternative machines. Numerical examples are given to demonstrate the use of the above algorithms.     

A capacitated vehicle routing problem with order available time in e-commerce industry

In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.     

Optimal flow path design of unidirectional AGV systems

This paper describes an alternative formulation of the AGV flow path layout (FPL) problem which was first formulated by Gaskins and Tanchoco (1987) as a zero-one integer programming problem. A computationally efficient procedure is proposed which is based on the branch-and-bound technique. An algorithm for satisfying the reachability condition for nodes in the AGV flow path network is also presented. A simple illustrative example is discussed to demonstrate the procedure, and a more complex problem is also given.     

Solving the facility and layout and location problem by ant-colony optimization-meta heuristic

This paper describes a heuristic algorithm for solving the plant/facility location problem by applying ant-colony optimization meta-heuristic. The facility location problem is discussed, and a mathematical formulation is presented. The problem is then modelled as a quadratic assignment problem. An ant algorithm is developed to solve the problem. The results reveal that the proposed algorithm can be adaptively constructed to solve discrete plant location problems. This has been applied to a set of known test problems and appears to be able to compete with other current solutions with encouraging results.     

研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法

现阶段,研发型企业的项目处于多项目环境下,为了解决多项目并行时人力资源争夺问题,本文针对该类企业多项目管理中人力资源调度进行优化研究,以考虑项目延期惩罚成本的最小总成本为目标函数,将现实问题抽象建模。基于国内外的研究提出了一种超启发式算法进行求解,该算法将人力资源调度问题分为项目活动分配和人员选择项目活动两个部分,采用蚁群优化作为高层启发式策略搜索低层启发式规则,再进一步根据规则解构造出可行解。最后本研究设计多组仿真实验与启发式规则进行对比,结果表明该算法有较好的搜索性能,为人力资源的调度问题提供了新的解决方案。     

A joint determination of storage locations and space requirements for correlated items in a miniload automated storage-retrieval system

We study the problem of clustering inventory items to assigned storage locations. Inventory-related cost as well as material-handling cost is considered to determine the space requirement and the storage location of each item simultaneously. An improvement heuristic algorithm is developed for the problem. We provide a numerical example to illustrate the algorithm developed. The performance of the algorithm is evaluated through numerical experimentation.     

An N-Product, Multi-Machine, Lotsize Scheduling Model

In this paper we consider an N-product, multi-machine, lotsize-scheduling problem that was originally encountered in a large automotive metal stamping facility. It is shown that the natural constraints of the real-life problem provide a special structure which allows an efficient formulation of the problem as a 0-1 integer program. An implicit enumeration algorithm for obtaining numerical solutions is presented. Computational experience shows that the algorithm is quite efficient when the number of products does not exceed ten or eleven. In the automotive metal stamping facility, that number is rarely exceeded; therefore, it is possible to employ the model as one of the basic tools used by a team responsible for the development of a production planning system.     

Analysis of inequality and residual flow procedures and an iterative scheme for free surface seepage

An efficient block overrelaxation algorithm is presented for the solution of the steady-state dam seepage problem. The formulation of Alt is used in conjunction with a finite element method on a fixed mesh to obtain a finite dimensional problem which is then solved by the algorithm. Some similarities of the formulation and the residual flow method of Desai are also discussed. Numerical results are compared with results of other authors.     

基于最小二乘法的曲面生成算法研究

针对不均匀截面线族曲面生成问题,本文提出了一种基于最小二乘法的曲面生成算法。这种算法在插值的思想上融合了逼近的思想,因此解决了困截面线旅不均匀而使曲面参数线族不合理并导致曲面光顺性不好的问题。该算法已在自行设计的面向数控的曲面造型系统中实现．     

A branch and bound algorithm for scheduling problem of a robot‐centered manufacturing cell

Abstract

An alternative formulation of the scheduling problem in a robot‐centered manufacturing cell has been described here, which was originally formulated by Lin et al. [7] as a mixed integer programming problem. An efficient procedure based on the branch and bound technique has been proposed. In order to reduce the complexity of the branching procedure, several sequencing rules [4] have been imbedded into the proposed procedure and an integrated algorithm has then been presented. The computational results have indicated the proposed algorithm to be efficient. Finally, conclusions and some suggestions are given.     

An Optimal Multi-Vector Iterative Algorithm in a Krylov Subspace for Solving the Ill-Posed Linear Inverse Problems

An optimal m-vector descent iterative algorithm in a Krylov subspace is developed, of which the m weighting parameters are optimized from a properly defined objective function to accelerate the convergence rate in solving an ill-posed linear problem. The optimal multi-vector iterative algorithm (OMVIA) is convergent fast and accurate, which is verified by numerical tests of several linear inverse problems, including the backward heat conduction problem, the heat source identification problem, the inverse Cauchy problem, and the external force recovery problem. Because the OMVIA has a good filtering effect, the numerical results recovered are quite smooth with small error, even under a large noise up to 10%.     

Structural damage identification using an enhanced thermal exchange optimization algorithm

The recently developed optimization algorithm—the so-called thermal exchange optimization (TEO) algorithm—is enhanced and applied to a damage detection problem. An offline parameter tuning approach is utilized to set the internal parameters of the TEO, resulting in the enhanced heat transfer optimization (ETEO) algorithm. The damage detection problem is defined as an inverse problem, and ETEO is applied to a wide range of structures. Several scenarios with noise and noise-free modal data are tested and the locations and extents of damages are identified with good accuracy.     

A branch and bound algorithm for the strip packing problem

We propose a new branch and bound algorithm for the two dimensional strip packing problem, in which a given set of rectangular pieces have to be packed into a strip of given width and infinite length so as to minimize the required height of the packing. We develop lower bounds based on integer formulations of relaxations of the problem as well as new bounds based on geometric considerations, and reduce the tree search with some dominance criteria. An extensive computational study shows the relative efficiency of the bounds and the good performance of the exact algorithm.     

A MODIFIED PATTERN SEARCH METHOD WITH RELAXED LEXICOGRAPHIC MINIMIZATION FOR ENGINEERING DESIGN

In engineering design, many design problems have multiple constraints and objectives, which may be non-differentiable. For this problem type, only zero-order solution methods are applicable. In this paper, a relaxed lexicographic pattern search method is presented for solving this design problem type, where the objectives are preferenced in either an Archimedean or preemptive formulation. The Hooke-Jeeves (HJ) pattern search method is the basis of this method, which is implemented as the MORPS (Multi-Objective Randomized Pattern Search) algorithm. The HJ pattern search method is used because it requires only function values and has an intuitive graphical interpretation through which to gain insight into the nature of complex design spaces. A relatively new class of simultaneous product/process design problem utilizing virtual prototypes to support design for disassembly is introduced to motivate the need for the MORPS algorithm. An example, based on the design of an automotive center console for disassembly, illustrates the application of the MORPS algorithm.     

A class of genetic algorithms for multiple-level warehouse layout problems

A new kind of warehouse layout problem, multiple-level warehouse layout problem (MLWLP), is investigated. Both horizontal and vertical travel costs need to be considered when making a layout. In the problem, unit travel costs are item-dependent and different items can be mixed in a cell. An IP model is proposed, which is shown to be NP-hard. An effective assignment method is presented and genetic algorithm heuristics developed. Extensive computational experiments are conducted to verify the effectiveness of the algorithms.     

Interval algorithm for global numerical optimization

The interval optimization algorithm shows great advantages in bound constrained global optimization. An interval algorithm is presented in this article based on a new selection criterion. The selection criterion is proposed based on numerical experiments and the parameter pf* designed by Casado, Garcia and Csendes in 2000. The proposed criterion at each iteration selects some intervals of which the number is not greater than a constant so that the possible memory problem during the implementation of the algorithm is avoided and the running time of the algorithm is decreased, when the dimension of the problem is increasing. Based on the selection criterion, the proposed algorithm is implemented for a wide set of tested functions which includes easy and hard problems. Numerical experiments show that the proposed algorithm is efficient.     

Use of boundary element method for the determination of tool shape in electrochemical machining

The problem of cathode shape determination for a given anode shape in electrochemical machining is considered. An algorithm based on the boundary integral equation technique and non-linear optimization for this inverse problem is developed. The additional flux condition at the anode is used as the constraint in this ill-posed problem. Through an iterative process, the shape of the cathode is determined by minimizing a functional. The algorithm is tested on two examples. It is shown that the algorithm is consistently superior compared to published numerical techniques based on the embedding method or the method of the lines.