A heuristic approach for transfer lines balancing

The paper deals with optimal balancing transfer lines where the operations in each workstation are grouped into blocks. All operations of the same block are executed simultaneously by one spindle head. Spindle heads of the same workstation are activated sequentially. The workstation time is the sum of the processing times of its blocks. The problem is to find the best assignment of operations to blocks and assignment of blocks to workstations that leads to the minimal transfer line cost (a weighted sum of blocks and workstation numbers). The solution must provide a desired productivity rate (cycle time). It must also satisfy precedence and compatibility constraints. Two heuristic algorithms based on the COMSOAL technique are proposed. Results from computer testing are reported.     

Enhanced mixed integer programming model for a transfer line design problem

Modular machining lines with multi-spindle workstations are considered. A multi-spindle head executes a set of operations. The problem of optimal design or reconfiguration of such lines is considered here. The set of all available spindle heads, operations executed by each spindle head, spindle head times and costs are assumed to be known. There are operations which can be executed by one of several candidate spindle heads, i.e., in different configuration with other operations. The problem consists in the choice of spindle heads from the given set and their assignment to workstations. The goal is to minimize the line cost while satisfying the precedence, inclusion and exclusion constraints. This problem is an extension of well known assembly line balancing and equipment selection problem. In our previous work, we proposed a MIP model which was significantly limited as to the size of the problems treated. In this paper, quite a few original approaches are suggested to improve the previous MIP model. The numerical tests reported show that the calculation time is drastically decreased, thereby expanding the model to larger and more realistic industrial problems.     

集装箱码头装卸作业的调度控制模型及算法设计

对集装箱码头上装卸作业的调度控制直接影响码头的整体运营效率．本文研究了集装箱码头装卸作业的调度控制问题,提出了一个基于柔性化flow shop的集成化控制模型．该问题具有非线性规划(NP：non- polynomial)难度,因此本文开发设计了两类基于优先级规则的启发式调度算法．利用该模型来对码头中多种装卸设备进行总体调度可以提高设备之间的协调性,提高码头效率,降低成本．实验研究证明算法能有效地解决该问题．     

OOESAlgorithm.jl: a julia package for optimizing a linear function over the set of efficient solutions for biobjective mixed integer linear programming

We present OOESAlgorithm.jl , a package for optimizing a linear function over the efficient set of biobjective mixed integer linear programs. The proposed package extends our recent study (see Sierra‐Altamiranda and Charkhgard [INFORMS Journal on Computing, https://doi.org/10.1287/ijoc.2018.0851]) by adding two main features: (a) in addition to CPLEX, the package allows employing any single‐objective solver supported by MathProgBase.jl , for example, GLPK, CPLEX, and SCIP; (b) the package supports execution on multiple processors and is compatible with the JuMP modeling language. An extensive computational study shows the efficacy of the package and its features.     

Inventory Minimization and Production Scheduling: the Case of a Large Hong Kong Company

The background of this study is a rather classical but complex inventory control/production planning/line scheduling problem of a major soft-drink company in Hong Kong. The issue that stands out for this many-product high-sales manufacturer is the storage space of its central warehouse, which often finds itself in the state of overflow or near capacity with finished goods and work-in-process inventory. This phenomenon can create immediate interruptions of production, capital tie-ups and subsequent potential of lost sales. Another obviously important concern is the meeting of forecast demands. A mathematical modelling approach that entails techniques of multi-period aggregate optimization is proposed to tackle the overall problem. The dual objectives are to achieve better production planning and line scheduling in order to minimize inventory build-up and maximize demand satisfaction. Numerical results for a sample problem are reported as an illustration to this proposed two-phase approach.     

Correspondence of projected 3‐D points and lines using a continuous GRASP

The field of computer vision has experienced rapid growth over the past 50 years. Many computer vision problems have been solved using theory and ideas from algebraic projective geometry. In this paper, we look at a previously unsolved problem from object recognition, namely object recognition when the correspondences between the object and image data are not known a priori. We formulate this problem as a mixed‐integer non‐linear optimization problem in terms of the unknown projection relating the object and image, as well as the unknown assignments of object points and lines to those in the image. The global optimum of this problem recovers the relationship between the object points and lines with those in the image. When certain assumptions are enforced on the allowable projections mapping the object into the image, a proof is provided which permits one to solve the optimization problem via a simple decomposition. We illustrate this decomposition approach on some example scenarios.