An efficient heuristic for the multi-vehicle one-to-one pickup and delivery problem with split loads

In this study, we consider the Multi-vehicle One-to-one Pickup and Delivery Problem with Split Loads (MPDPSL). This problem is a generalization of the one-to-one Pickup and Delivery Problem (PDP) where each load can be served by multiple vehicles as well as multiple stops by the same vehicle. In practice, split deliveries is a viable option in many settings where the load can be physically split, such as courier services of third party logistics operators. We propose an efficient heuristic that combines the strengths of Tabu Search and Simulated Annealing for the solution of MPDPSL. Results from experiments on two problems sets in the literature indicate that the heuristic is capable of producing good quality solutions in reasonable time. The experiments also demonstrate that up to 33\% savings can be obtained by allowing split loads; however, the magnitude of savings is dependent largely on the spatial distribution of the pickup and delivery points

Exact solution procedures for the balanced unidirectional cyclic layout problem

In this paper, we consider the balanced unidirectional cyclic layout problem (BUCLP) arising in the determination of workstation locations around a closed loop conveyor system, in the allocation of cutting tools on the sites around a turret, in the positioning of stations around a unidirectional single loop AGV path. BUCLP is known to be NP-Complete. One important property of this problem is the balanced material flow assumption where the material flow is conserved at every workstation. We first develop a branch-and-bound procedure by using the special material flow property of the problem. Then, we propose a dynamic programming algorithm, which provides optimum solutions for instances with up to 20 workstations due to memory limitations. The branch and bound procedure can solve problems with up to 50 workstations.

A Genetic Algorithm for the Traveling Salesman Problem with Pickup and Delivery Using Depot Removal and Insertion Moves

In this work, we consider the Traveling Salesman Problem with Pickup and Delivery (TSPPD), which is an extension of the well-known NP-hard Traveling Salesman Problem. We propose a Genetic Algorithm (GA) based on a specially tailored tour improvement procedure for the TSPPD. Computational experiments are reported on the test instances taken from the literature. The experimental results suggest that the proposed GA yields a promising performance in terms of both accuracy and efficiency compared to existing algorithms in the literature

Maximum weight perfect matching problem with additional disjunctive conflict constraints

We focus on an extension of the maximum weight perfect matching problem with additional disjunctive conflict constraints in conjunction with the degree and binary restrictions. Given a simple graph with a nonnegative weight associated with each edge and a set of conflicting edges, the perfect matching problem with conflict constraints consists of finding a maximum weight perfect matching without any conflicting edge pair. Unlike the well-known ordinary maximum weight perfect matching problem this one is strongly (Formula presented.) -hard. We propose two branch-and-bound algorithms for the exact solution of the problem. The first one is based on an equivalent maximum weight stable set formulation with an additional cardinality restriction obtained on the graph representing conflict relations and uses the information coming from its maximal stable sets. The second one is essentially a recursive depth first search scheme that benefits from simple upper bounds incorporated with a fast infeasibility detection procedure to prune the branch-and-bound tree. According to the extensive computational tests it is possible to say that they are both very efficient

Branch and bound algorithms for solving the multi-commodity capacitated multi-facility Weber problem

The Multi-commodity Capacitated Multi-facility Weber Problem is concerned with locating I capacitated facilities in the plane in order to satisfy the demands of J customers for K commodities such that the total transportation cost is minimized. This is a multi-commodity extension of the well-known Capacitated Multi-facility Weber Problem and difficult to solve. In this work, we propose two branch-and-bound algorithms for exactly solving this nonconvex optimization problem. One of them considers partitioning of the allocation space while the other one considers partitioning of the location space. We have implemented two lower bounding schemes for both algorithms and tested several branching strategies. The results of an extensive computational study are also included

Determining key capabilities in technology management using fuzzy analytic hierarchy process: a case study of Turkey

The importance of technology management is a vital determinant of long-run success or failure of organizations in today's world. Since technology is a major driver of the global economic development, business professionals seek more effective ways to manage existing and emerging technology. This study proposes a model to understand the links between competitive advantages, competitive priorities and competencies of a firm in the context of the technology management. We use the fuzzy analytical hierarchy process (AHP) to analyze these links. Moreover, we examine the perception of a group of managers from different Turkish firms regarding the technology management. The main result of this paper is that the concept of the management of technology arises to be much more important than both the product technology and the process technology

Location and allocation based branch and bound algorithms for the capacitated multi-facility Weber problem

\u3cp\u3eGiven the locations of J customers, their demands and I capacitated facilities, the Capacitated Multi-facility Weber Problem (CMWP) is concerned with locating I facilities in the plane to satisfy the demand of J customers with the minimum total transportation cost which is proportional to the distance between them. We propose two types of branch and bound algorithms for the ℓ\u3csub\u3er\u3c/sub\u3e distance CMWP with 1≤r<∞. One of them is an allocation space based branch and bound algorithm for which a new branching variable selection strategy and new lower bounding procedures have been proposed. The other one is new and partitions the location space. Based on extensive computational experiments we can say that the proposed algorithms are promising and perform better than the existing ones.\u3c/p\u3

Efficient approximate solution methods for the multi-commodity capacitated multi-facility Weber problem

\u3cp\u3eThe capacitated multi-facility Weber problem is concerned with locating I capacitated facilities in the plane to satisfy the demand of J customers with the minimum total transportation cost of a single commodity. This is a nonconvex optimization problem and difficult to solve. In this work, we focus on a multi-commodity extension and consider the situation where K distinct commodities are shipped subject to capacity constraints between each customer and facility pair. Customer locations, demands and capacities for each commodity, and bundle restrictions are known a priori. The transportation costs, which are proportional to the distance between customers and facilities, depend on the commodity type. We address several locationallocation and discrete approximation heuristics using different strategies. Based on the obtained computational results we can say that the alternate solution of location and allocation problems is a very efficient strategy; but the discrete approximation has excellent accuracy.\u3c/p\u3

Solving a minisum single facility location problem in three regions with different norms

The single facility location problem in multiple regions with different norms (SMDN) generalizes the well-known Weber Problem. The SMDN consists of finding the optimum location of a single facility in the plane which is partitioned into multiple regions where the distance to travel in each region is measured or approximated with different norms. In this study, we specifically focus on the SMDN considering three regions with either rectilinear or Euclidean norms. We first introduce some analytical properties of this problem. Then, we devise a specially tailored branch-and-bound algorithm, i.e. a Big Square Small Square algorithm (BSSS), and two heuristics, named as Discrete Approximation algorithm (DA) and Modified Weiszfeld procedure (MW). The performance of the proposed approaches are tested using both standard test instances from the literature and randomly generated instances. According to our extensive computational experiments, the BSSS stands out to be a suitable exact solution approach in terms of both accuracy and efficiency when commercial mixed integer nonlinear solvers are not applicable. Besides, we also observe that the DA yields quite accurate solutions at the expense of high computation times while the MW arises to be the most efficient method with the least accuracy

Assignment problem with conflicts

\u3cp\u3eWe focus on an extension of the assignment problem with additional conflict (pair) constraints in conjunction with the assignment constraints and binary restrictions. Given a bipartite graph with a cost associated with each edge and a conflict set of edge pairs, the assignment problem with conflict constraints corresponds to finding a minimum weight perfect matching without any conflicting edge pair. For example, some chemicals cannot be processed on close processors, food and toxic products cannot be stored neighboring locations at the same storage area, and machines cannot be sent to process jobs without satisfying some spatial constraints. Unlike the well-known assignment problem, this problem is NP-hard. We first introduce a realistic special class and demonstrate its polynomial solvability. Then, we propose a Branch-and-Bound algorithm and a Russian Doll Search algorithm using the assignment problem relaxations for lower bound computations, and introduce combinatorial branching rules based on the conflicting edges in an optimal solution of the relaxations. According to the extensive computational experiments we can say that the proposed algorithms are very efficient.\u3c/p\u3