An improved heuristic approach for multi-objective facility layout problem

Multi-objective facility layout problem (mFLP) generates a different layout by varying objectives weights. Since the selection of objective weights in mFLP is critical, stages of designing layout having multiple objectives, the objective weights therefore play an important role in the layout design of mFLP. In practice, it is selected randomly by the layout designer based on his/her past experience that restricts the layout designing process completely designer dependent and thus the layout varies from designer to designer. This paper aims to resolve the issues of selecting the objective weight for each objective. We propose four methods to determine objective weight which makes the design process of mFLP completely designer independent.     

Two new heuristic algorithms for the maximal planar layout problem

The adjacency problem is an important subproblem in facility layout planning. It is known to be NP-complete, so heuristics are required to solve large problem instances. In this paper two new heuristics for the adjacency problem are introduced which belong to a special class of constructive methods called Triangulation Expansion Heuristics. Extensive numerical experiments have been carried out in order to evaluate the proposed methods in terms of computing times and solution quality. It has been found that at least one method is clearly superior to the best methods proposed in the literature so far (Eades et al. 1982, Leung 1992).     

An efficient local search heuristic for the double row layout problem with asymmetric material flow

The double row layout problem (DRLP) consists of arranging a number of rectangular machines of varying widths on either side of a corridor to minimize the total cost of material handling for products that move between these machines. This problem arises in the context of many production environments, most notably semiconductor manufacturing. Because the DRLP contains both combinatorial and continuous aspects, traditional solution approaches are not well suited to obtain solutions within a reasonable time. Moreover, previous approaches to this problem did not consider asymmetric flows. In this paper, an effective local search procedure featuring linear programming is proposed for solving the DRLP with asymmetric flows (symmetric flows being a special case). This approach is compared against several constructive heuristics and solutions obtained by a commercial mixed integer linear programming solver to evaluate its performance. Computational results show that the proposed heuristic is an effective approach, both in terms of solution quality and computational effort.     

An improved version of the production switching heuristic for the aggregate production planning problem

The production switching heuristic (PSH) is recognized as an effective solution method for the aggregate production planning problem in industries where production is limited to discrete levels. However, we find that the PSH is not sufficiently responsive to demand fluctuation and tends to make belated decisions. This shortcoming stems mainly from the switching mechanism. This paper proposes an improved version of the PSH. The heuristic uses an improved switching mechanism which can be shown to dominate the PSH. The effectiveness of the proposed heuristic is investigated with several well known problems including the paint factory problem. The results are compared with those of the linear decision rule and the linear programming model as well as the PSH.     

A genetic algorithm based heuristic for adjacent paper-reel layout problem

In this paper, we present an algorithm that solves a paper reel layout problem where the available space is divided into equal-size cells. The problem is to find a layout with the minimum transportation cost subject to adjacency and other constraints. A genetic algorithm is used in a two-stage iterative approach to solve the problem. Computational results seem to indicate the efficiency and effectiveness of the proposed solution method.     

New Tabu search heuristics for the dynamic facility layout problem

A manufacturing facility is a dynamic system that constantly evolves due to changes such as changes in product demands, product designs, or replacement of production equipment. As a result, the dynamic facility layout problem (DFLP) considers these changes and is defined as the problem of assigning departments to locations during a multi-period planning horizon such that the sum of the material handling and re-arrangement costs is minimised. In this paper, three tabu search (TS) heuristics are presented for this problem. The first heuristic is a simple TS heuristic. The second heuristic adds diversification and intensification strategies to the first, and the third heuristic is a probabilistic TS heuristic. To test the performances of the heuristics, two sets of test problems from the literature are used in the analysis. The results show that the second heuristic out-performs the other proposed heuristics and the heuristics available in the literature.     

A sequence-pair representation and MIP-model-based heuristic for the facility layout problem with rectangular departments

In Facility Layout Problem (FLP) research, the continuous-representation-based FLP can consider all feasible all-rectangular-department solutions. Given this flexibility, this representation has become the representation of choice in FLP research. Much of this research is based on a methodology of Mixed-Integer Programming (MIP) models. However, these MIP-FLP models can only solve problems with a limited number of departments to optimality due to the large number of combinations of the binary variables used in the models to maintain feasibility with respect to departments overlapping. Our research centers around the sequence-pair representation, a concept that originated in the Very Large Scale Integration (VLSI) design literature. We show that an exhaustive search of the sequence-pair solution space will result in finding the optimal layout of the MIP-FLP and that every sequence-pair solution is position consistent (although possibly not layout feasible) in the MIP-FLP. We propose a genetic-algorithm-based heuristic that combines the sequence-pair representation with the MIP-FLP model. Numerical experiments based on different sized test problems from both the literature and industrial applications are provided and the solutions are compared with both the optimal solutions and the solutions from other heuristics to show the effectiveness and efficiency of our heuristic. For 11 data sets from the literature we provide solutions better than those previously found. For two large industrial application data sets we perform a sensitivity analysis with respect to the department aspect ratio constraint.     

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.     

A heuristic approach on the facility layout problem based on game theory

Facility layout problems are related to the location of all facilities in a plant. Numerous research works related to facility layout have been published. The applicability of these various existing models may be limited by the fact that they all ignore competitive reactions to one's actions. In addition to external competitors, some internal problems of system such as material handling system design affect layout designs. For considering these effects, some researchers have investigated multi-objective approaches that in most cases lead to the optimisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and quantifying the weights. To the extent that competitors do react to a firm's actions and also the facility layout problem considers several conflicting objectives by distinct decision makers in the firm, the existing models may be oversimplifications of reality. In this paper, we modelled such a facility layout problem with conflicting objectives under a duopoly Bertrand competition as a game and solved it with a proposed simulated annealing meta-heuristic. Results obtained from solving some numerical examples confirm the effectiveness of the proposed model for the layout design.     

Two graph-theoretic procedures for an improved solution to the facilities layout problem

A new operation, referred to as the T-operation, for replacing edges of the maximal planar graph is presented. Cases of this operation are discussed. It is then used to develop two graph-theoretic improvement procedures for solving facilities layout problems. Both procedures can be employed to improve solutions of any existing graph-theoretic construction heuristic. A computational experiment is reported for a series of test problems which indicates that both procedures can considerably improve the initial solutions in a cost-effective manner. Since they are simple and effective, realistically sized facilities layout problems can be solved efficiently by their use.     

A dynamic programming-based heuristic for the variable sized two-dimensional bin packing problem

This paper addresses a variable sized two-dimensional bin packing problem. We propose two heuristics, H1 and H2, stemming from the dynamic programming idea by aggregating states to avoid the explosion in the number of states. These algorithms are elaborated for different purposes: H1 builds a general packing plan for items, while H2 can provide solutions by considering a variety of customer demands, such as guillotine cutting style and rotation of items. The performance of both algorithms is evaluated based on randomly generated instances reported in the literature by comparing them with the lower bounds and optimal solutions for identical bins. Computational results show that the average gaps are 8.97% and 13.41%, respectively, for H1 and H2 compared with lower bounds, and 5.26% and 6.26% compared with optimal solutions for identical bins. We also found that we can save 6.67% of space, on average, by considering variable sized bins instead of a bin packing problem with identical bins.     

International facilities location: A heuristic procedure for the dynamic uncapacitated problem

It is now well known that most major companies no longer operate in a single market. To penetrate global markets and obtain their benefits, companies are under tremendous pressure to reduce the price of their products, and thus their production and material costs. When a foreign location is used, the components of a product are produced there and final assembly takes place either at the foreign location or at the parent domestic plant. This paper first presents the issues related to international facilities location (IFL) problems, and provides the framework required to deal with such problems. It then presents a heuristic algorithm for solving the IFL problem. Extensive computational experience was gained by solving a variety of IFL problems of different sizes.     

An improved facility layout construction method

This study presents a new distance-based facility layout construction technique. Given a two-dimensional (i.e. single-floor) facility layout construction problem in which the order of placement of individual departments is known (a challenging problem in itself), the technique presented herein proposes the use of sub-departments and expected distance functions instead of centroid-to-centroid distances for the placement of departments. In this paper an expected distance function is defined as the probabilistic expectation of the particular distance metric of interest (rectilinear, Euclidean, etc.) in which the parameters involved are defined by random vectors in 2-dimensional Euclidean space. This study presents an enhanced facility layout construction technique that incorporates several enhancements over the well-known systematic layout procedure (SLP). The goal herein is to minimise the error induced by the use of the centroid-to-centroid distances between the departments inherent to the SLP.     

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10–30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine–cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.     

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 improved memetic algorithm based on a dynamic neighbourhood for the permutation flowshop scheduling problem

The permutation flowshop scheduling problem (PFSP) has been extensively studied in the scheduling literature. In this paper, we present an improved memetic algorithm (MA) to solve the PFSP to minimise the total flowtime. In the proposed MA, we develop a stochastic local search based on a dynamic neighbourhood derived from the NEH method. During the evolution process, the size of the neighbourhood is dynamically adjusted to change the search focus from exploration to exploitation. In addition, we introduce a new population generation mechanism to guarantee both the quality and diversity of the new populations. We also design a diversity index for the population to monitor the diversity of the current population. If the diversity index is less than a given threshold value, the current population will be replaced by a new one with good diversity so that the proposed MA has good ability to overcome local optima. We conduct computational experiments to test the effectiveness of the proposed algorithm. The computational results on randomly generated problem instances and benchmark problem instances show that the proposed MA is effective and superior or comparable to other algorithms in the literature.     

An improvement heuristic framework for the laser cutting tool path problem

This paper deals with generating cutting paths for laser cutting machines by representing a tool path in a novel way. Using the new representation, the tool path problem can be viewed as finding a partitioning of contours which minimises the sum of the costs of a rooted directed minimum spanning tree to connect the partitions and the costs of a generalised travelling salesman problem (GTSP) solutions within each partition. Using Edmond–Liu’s algorithm to solve the arborescence problem, an improved Lin–Kernighan heuristic to solve the GTSP and a heuristic-repartitioning approach, tool paths can be generated that are 4.2% faster than those generated by an existing tool path construction heuristic.     

An iterated-local-search heuristic for the resource-constrained weighted earliness-tardiness project scheduling problem

This paper deals with the weighted earliness-tardiness resource-constrained project scheduling problem with minimum and maximum time lags (WET-RCPSP/max). The problem consists of scheduling the activities of a project subject to prescribed resource and temporal constraints such that the total weighted deviation of the activities' completion times from prescribed due dates is minimized. Key applications are planning of just-in-time production and reactive scheduling. For the (approximative) solution of the WET-RCPSP/max, we present a population-based iterated-local-search heuristic. We also report the results of an experimental performance analysis where this heuristic outperformed state-of-the-art methods.     

An extension of Palmer's heuristic for the flow shop scheduling problem

We describe a simple modification of Palmer's heuristic for scheduling jobs in a flow shop. While the additional computation required is relatively small, the performance of the algorithm compares very well with that of the more sophisticated and better algorithm of Campbell, et al. (1970) at a fraction of the effort required by the latter.     

Optimal and heuristic algorithms for the multi-location dynamic transshipment problem with fixed transshipment costs

We consider centrally controlled multi-location systems, which coordinate their replenishment strategies through the use of transshipments. In a dynamic deterministic demand environment the problem is characterized by several locations, each of which has known demand for a single product for each period in a given finite horizon. We consider replenishment, transshipment and inventory holding costs at each location, where the first two have location-dependent fixed, as well as linear components, and the third is linear and identical to all locations. We prove that the resulting dynamic transshipment problem is NP-hard, identify a special structure which is satisfied by an optimal solution and develop, based on this structure, an exponential time algorithm to solve the problem optimally. In addition, we develop a heuristic algorithm, based on partitioning the time horizon, which is capable of solving larger instances than the optimal solution. Our computational tests demonstrate that the heuristic performs extremely well.