The segmented bidirectional single-loop topology for material flow systems

This paper introduces the segmented bidirectional single-loop (SBSL) flow topology for carrier-based material handling systems. This configuration is based on a single-loop flow-path structure that is divided into non-overlapping segments, each containing a single carrier operating in a bidirectional mode. The design procedure comprises a 0 - 1 mixed-integer formulation to determine the single-loop including the pickup and delivery station location. The second stage is a segmentation procedure to determine the non-overlapping segments in the loop. Finally the performance of the SBSL is evaluated by means of simulation.     

Developing exact and Tabu search algorithms for simultaneously determining AGV loop and P/D stations in single loop systems

There are some issues which have to be addressed when designing an automated guided vehicles system (AGVS) such as flow-path layout, traffic management, the number and the location of pick up and delivery points, vehicle routing and so on. One of the AGVS guide path configurations discussed in the previous researches includes a single-loop which is the subject of this paper. In unidirectional single loop systems, determining the loop for the motion of an AGV, and the location of pick up and delivery (P/D) stations in the cells, are prominent points which, when considered simultaneously, lead to better results than determining each one independently. However, in the literature it is proved that the problem of separately determining the shortest feasible loop is a NP-complete problem. In this paper, by considering a from-to chart and a block layout as the input of problem, we try to determine: (1) a single loop, with at least one shared edge with each cell, (2) the direction of the flow and (3) the location of P/D stations on the loop, all at the same time, in a way that the total travel distance on the loop be minimised. In this regard, first a new exact algorithm is presented and then three heuristic algorithms are developed utilising a Tabu search (TS) method. Solving randomly generated test problems shows that our exact algorithm is capable of solving small size problems; also all three TS algorithms work efficiently in solving problems that could not be solved by exact algorithms.     

An integrated approach to determine the block layout,AGV flow path and the location of pick-up/delivery points in single-loop systems

Layout design and material handling system design are two of the major aspects of facility planning. Although both aspects directly influence each other, the classical approach to the layout design is carried out in two separate steps: in the first step the block layout, i.e. the location of the departments in the workshop, is constructed, and in the second step, the material handling system is designed. The separate optimisation of these two aspects of the problem leads to solutions that can be far from the global optimum. In this paper, we develop an integrated algorithm to design the facilities and material handling systems. We focus on single-loop AGV systems. The proposed algorithm determines the block layout, AGV single-loop flow path and pick-up delivery stations, simultaneously. The associated from–to chart and the area of departments are the principal inputs of the algorithm. The objective is minimising total material flow distance among all departments. The results of our computational experiments show the algorithm was coded using MATLAB 7.0, and that our integrated algorithm is more efficient in terms of both the objective function value and the runtime.     

An o(n) complexity recursive algorithm for multi‐flexible‐body dynamics based on absolute nodal coordinate formulation

A new algorithm called recursive absolute nodal coordinate formulation algorithm (REC‐ANCF) is presented for dynamic analysis of multi‐flexible‐body system including nonlinear large deformation. This method utilizes the absolute nodal coordinate formulation (ANCF) to describe flexible bodies, and establishes a kinematic and dynamic recursive relationship for the whole system based on the articulated‐body algorithm (ABA). In the ordinary differential equations (ODEs) obtained by the REC‐ANCF, a simple form of the system generalized Jacobian matrix and generalized mass matrix is obtained. Thus, a recursive forward dynamic solution is proposed to solve the ODEs one element by one element through an appropriate matrix manipulation. Utilizing the parent array to describe the topological structure, the REC‐ANCF is suitable for generalized tree multibody systems. Besides, the cutting joint method is used in simple closed‐loop systems to make sure the O(n) algorithm complexity of the REC‐ANCF. Compared with common ANCF algorithms, the REC‐ANCF has several advantages: the optimal algorithm complexity (O(n)) under limited processors, simple derivational process, no location or speed constraint violation problem, higher algorithm accuracy. The validity and efficiency of this method are verified by several numerical tests. Copyright © 2016 John Wiley & Sons, Ltd.     

AN OPTIMIZATION METHOD FOR THE DESIGN OF LARGE,HIGHLY CONSTRAINED COMPLEX SYSTEMS

A practical and efficient optimization method for the rational design of large, highly constrained complex systems is presented. The design of such systems is iterative and requires the repeated formulation and solution of an analysis model, followed by the formulation and solution of a redesign model. The latter constitutes an optimization problem. The versatility and efficiency of the method for solving the optimization problem is of fundamental importance for a successful implementation of any rational design procedure.

In this paper, a method is presented for solving optimization problems formulated in terms of continuous design variables. The objective function may be linear or non-linear, single or multiple. The constraints may be any mix of linear or non-linear functions, and these may be any mix of inequalities and equalities. These features permit the solution of a wide spectrum of optimization problems, ranging from the standard linear and non-linear problems to a non-linear problem with multiple objective functions (goal programming). The algorithm for implementing the method is presented in sufficient detail so that a computer program, in any computing language, can be written.     

The Stochastic Uncapacitated Facility Location Problem: A New Formulation and Extensions to the Capacitated Problem

This note presents an alternative formulation of the deterministic location model which Tcha and Yoon have recently developed to approximate the stochastic uncapacitated facility location problem. The model, besides being more compact and easier to handle than their model, has the distinct advantage of having a tighter LP relaxation. Also suggested is how the new formulation can be implemented in Van Roy's Cross Decomposition method for solving a more general stochastic capacitated problem.     

An approximate sensitivity analysis of results from complex computer models in the presence of epistemic and aleatory uncertainties

This paper focuses on sensitivity analysis of results from computer models in which both epistemic and aleatory uncertainties are present. Sensitivity is defined in the sense of “uncertainty importance” in order to identify and to rank the principal sources of epistemic uncertainty. A natural and consistent way to arrive at sensitivity results in such cases would be a two-dimensional or double-loop nested Monte Carlo sampling strategy in which the epistemic parameters are sampled in the outer loop and the aleatory variables are sampled in the nested inner loop. However, the computational effort of this procedure may be prohibitive for complex and time-demanding codes. This paper therefore suggests an approximate method for sensitivity analysis based on particular one-dimensional or single-loop sampling procedures, which require substantially less computational effort. From the results of such sampling one can obtain approximate estimates of several standard uncertainty importance measures for the aleatory probability distributions and related probabilistic quantities of the model outcomes of interest. The reliability of the approximate sensitivity results depends on the effect of all epistemic uncertainties on the total joint epistemic and aleatory uncertainty of the outcome. The magnitude of this effect can be expressed quantitatively and estimated from the same single-loop samples. The higher it is the more accurate the approximate sensitivity results will be. A case study, which shows that the results from the proposed approximate method are comparable to those obtained with the full two-dimensional approach, is provided.     

A new decomposition algorithm for a liquefied natural gas inventory routing problem

We consider an inventory routing problem (IRP) in the liquefied natural gas (LNG) supply chain, called the LNG-IRP. Here, an actor is responsible for the LNG production and inventory management at the liquefaction plants, the routing and scheduling of a heterogeneous fleet of LNG ships, as well as the inventories and sales at the regasification terminals. Furthermore, all ports have a limited number of berths available for loading and unloading. The LNG-IRP is more complicated than many other maritime inventory routing problems because a constant rate of the cargo evaporates in the tanks each day and is used as fuel during transportation. In addition, a variable number of tanks are unloaded at the regasification terminals. We introduce a new path flow formulation for this problem arising from a novel decomposition scheme based on parts of a ship schedule, called duties. A ship schedule for the entire planning horizon can be divided into duties consisting of a visit to a liquefaction plant, then one or two visits to a regasification terminal before ending in a liquefaction plant. The solution method suggested is based on a priori generation of duties, and the formulation is strengthened by valid inequalities. The same problem was previously solved by a branch-price-and-cut algorithm for a schedule-based formulation. Computational results show that the new formulation provides tighter bounds than the previous schedule-based formulation. Furthermore, on a set of 27 benchmark instances, the proposed algorithm clearly outperforms the previous branch-price-and-cut algorithm both with regard to computational time and the number of problems solved within a 10-h time limit.     

A capacitated facility location problem with constrained backlogging probabilities

One of the assumptions of the capacitated facility location problem (CFLP) is that demand is known and fixed. Most often, this is not the case when managers take some strategic decisions such as locating facilities and assigning demand points to those facilities. In this paper we consider demand as stochastic and we model each of the facilities as an independent queue. Stochastic models of manufacturing systems and deterministic location models are put together in order to obtain a formula for the backlogging probability at a potential facility location. Several solution techniques have been proposed to solve the CFLP. One of the most recently proposed heuristics, a reactive greedy adaptive search procedure, is implemented in order to solve the model formulated. We present some computational experiments in order to evaluate the heuristics’ performance and to illustrate the use of this new formulation for the CFLP. The paper finishes with a simple simulation exercise.     

Mixed model assembly system with multiple secondary feeder lines: layout design and balancing procedure for ATO environment

The constant research for efficiency and flexibility has forced assembly systems to change from simple/single assembly lines to mixed model assembly lines, while the necessity to reduce inventory has led the transition from single to multi-line systems, where some components are assembled in secondary lines, called feeder lines, connected to the main one by a ‘pull philosophy’. A possible approach to configure such an assembly system is to balance the main line first and use the retrieved cycle time to balance each feeder line separately, which is a questionable solution, especially if operators can perform tasks on both the feeder and the main line. Moreover for its complexity the mixed model balancing problem is usually solved transforming it into a single model by creating a single ‘virtual average model’, representative of the whole production mix. The use of a virtual average model assumes that the processing times of some models are higher or lower than the cycle time, which creates overload/idle time at the stations. This approach, especially in complex multi line production systems, largely reduces the assembly line productivity and increases the buffers dimensions. This paper faces the mixed model assembly line balancing problem in the presence of multiple feeder lines, introducing an innovative integrated main-feeder lines balancing procedure in case of unpaced assembly systems. The proposed approach is compared with the classical one and validated through simulation and industrial applications.     

Dual boundary element analysis of cracked plates: singularity subtraction technique

The present paper is concerned with the formulation of the singularity subtraction technique in the dual boundary element analysis of the mixed-mode deformation of general homogeneous cracked plates.The equations of the dual boundary element method are the displacement and the traction boundary integral equations. When the displacement equation is applied on one of the crack surfaces and the traction equation is applied on the other, general mixed-mode crack problems can be solved in a single region boundary element formulation, with both crack surfaces discretized with discontinuous quadratic boundary elements.The singularity subtraction technique is a regularization procedure that uses a singular particular solution of the crack problem to introduce the stress intensity factors as additional problem unknowns. The single-region boundary element analysis of a general crack problem restricts the availability of singular particular solutions, valid in the global domain of the problem. A modelling strategy, that considers an automatic partition of the problem domain in near-tip and far-tip field regions, is proposed to overcome this difficulty. After the application of the singularity subtraction technique in the near-tip field regions, regularized locally with the singular term of the Williams' eigenexpansion, continuity is restored with equilibrium and compatibility conditions imposed along the interface boundaries. The accuracy and efficiency of the singularity subtraction technique make this formulation ideal for the study of crack growth problems under mixed-mode conditions.     

An extended distance-based facility layout problem

The distance-based facility layout problem with unequal-area departments has been studied by many researchers for over 30 years. Still, current approaches require certain assumptions that limit the type of solutions obtained. In this paper, we consider manufacturing systems in which replicates of the same machine type may exist in the facility, and propose an extended distance-based facility layout problem that concurrently determines the number and shape of the departments, the assignment of machines to departments, and the allocation of part flow volume to individual machines. A non-linear mixed-integer program that accurately captures the extended facility layout and part flow allocation problem, a decomposition approach that exploits the structure of the formulation using a heuristic solution procedure, as well as computational results that evaluate the proposed approach, are presented.     

An Enhanced Formulation of the Maximum Entropy Method for Structural Optimization

A numerical optimization method was proposed time ago by Templeman based on the maximum entropy principle. That approach combined the Kuhn-Tucker condition and the information theory postulates to create a probabilistic formulation of the optimality criteria techniques. Such approach has been enhanced in this research organizing the mathematical process in a single optimization loop and linearizing the constraints. It turns out that such procedure transforms the optimization process in a sequence of systems of linear equations which is a very efficient way of obtaining the optimum solution of the problem. Some examples of structural optimization, namely, a planar truss, a spatial truss and a composite stiffened panel, are presented to demonstrate the capabilities of the methodology.     

Analysis of crack closure problem using the dual boundary element method

A numerical procedure of the crack closure problem solved by the dual boundary element method is developed in this paper. The dual boundary element method is used to allow for the solution to a general mixed-mode crack problem with a single regional formulation. The frictional contact problem on the crack surface is formulated with the complementary problem adapting the Coulomb's friction law. Several examples are shown to demonstrate the validity of the present procedure.     

Campaign planning in time-indexed model formulations

This paper deals with a production planning problem typical for process industries. There the production amount of one continuous production run – referred to as a campaign – is often constrained by a lower and/or upper bound or such that it has to be in multiples of a predefined batch size. For this kind of problem, a new mixed-integer-programming model formulation is proposed that is based on a standard lot-sizing model with uniform time buckets. Thereby the concept of time continuity is integrated into a standard bucket-oriented lot-sizing model formulation. Furthermore, some algorithmic (valid inequalities) and modelling enhancements to the formulation are presented. Extensive computational tests show that this new model formulation clearly outperforms a benchmark model formulation. Moreover, they show the additional computational effort associated with different types of restrictions imposed on campaigns.     

Truss layout design under nonprobabilistic reliability-based topology optimization framework with interval uncertainties

A nonprobabilistic reliability-based topology optimization (NRBTO) method for truss structures with interval uncertainties (or unknown-but-bounded uncertainties) is proposed in this paper. The cross-sectional areas of levers are defined as design variables, while the material properties and external loads are regard as interval parameters. A modified perturbation method is applied to calculate structural response bounds, which are the prerequisite to obtain structural reliability. A deviation distance between the current limit state plane and the objective limit state plane, of which the expression is explicit, is defined as the nonprobabilistic reliability index, which serves as a constraint function in the optimization model. Compared with the deterministic topology optimization problem, the proposed NRBTO formulation is still a single-loop optimization problem, as the reliability index is explicit. The sensitivity results are obtained from an analytical approach as well as a direct difference method. Eventually, the NRBTO problem is solved by a sequential quadratic programming method. Two numerical examples are used to testify the validity and effectiveness of the proposed method. The results show significant effects of uncertainties to the topology configuration of truss structures.     

Genetic algorithm-based approach for fixed and switchable capacitors placement in distribution systems with uncertainty and time varying loads

Installation of capacitors in primary and secondary networks of distribution systems is one of the efficient methods for energy and peak load loss reduction. Also voltage profile in the feeder is improved and static voltage stability is enhanced. The main challenge is the determination of optimal location and size of fixed and switchable capacitors with respect to network configuration, distribution of load in the feeder, time variation of load and uncertainty in load forecasting or load allocation process. To solve this complex problem, an efficient method for simultaneous allocation of fixed and switchable capacitors in radial distribution systems is presented. Energy and peak load loss reduction, and capacitor cost are considered in the cost function. Time variation and uncertainty of load are also involved in problem formulation. Genetic algorithm with a new coding as two rows chromosomes is used for optimisation. Numerical studies show the effectiveness of the proposed procedure     

A multi-factor plant layout methodology

This paper presents a formulation for the plant layout problem, incorporating more than two input factors that may be either qualitative or quantitative in nature. A heuristic is presented which combines a construction and improvement procedure to quickly develop a good layout from the formulation. The output layout from the heuristic may be used directly as the final layout or it may be used as a good starting layout for any other computerized layout improvement procedure. The heuristic is illustrated with a practical example of a large plant with 36 departments.     

A capacitated vehicle routing problem for just-in-time delivery

This paper focuses on the formulation and solution of the problem of planning vehicle routes for material delivery within the premises of a plant working under a just-in-time production system. The unique characteristic of this problem is that the quantity to be delivered at each of the demand nodes is a function of the route taken by the vehicle assigned to serve that node. The problem is modeled by adding a non-linear capacity constraint to the standard vehicle routing model, such that vehicle idle times and inventories at the customer locations are minimized. A heuristic solution procedure is outlined, and the formulation of a lower-bound relaxation is suggested. The performance of the heuristic solution procedure is evaluated in comparison to the lower-bound relaxation, and the heuristic procedure is shown to provide generally good results.     

A decomposition procedure for large-scale optimum plastic design problems

A decomposition procedure is proposed in this paper for solving a class of large-scale optimum design problems for perfectly-plastic structures under several alternative loading conditions. The conventional finite element method is used to cast the problem into a finite dimensional constrained nonlinear programming problem. Structures of practically meaningful size and complexity tend to give rise to a large number of variables and constraints in the corresponding mathematical model. The difficulty is that the state-of-the-art mathematical programming theory does not provide reliable and efficient ways of solving large-scale constrained nonlinear programming problems. The natural idea to deal with the large-scale structural problem is somehow to decompose the problem into a collection of small-size problems each of which represents an analysis of the behaviour of each finite element under a single loading condition. This paper proposes one such way of decomposition based on duality theory and a recently developed iterative algorithm called the proximal point algorithm.