Customer Locations Research Articles

Locating service facilities to reduce lost demand

We analyze the problem of locating a set of service facilities on a network when the demand for service is stochastic and congestion may arise at the facilities. We consider two potential sources of lost demand: (i) demand lost due to insufficient coverage; and (ii) demand lost due to congestion. Demand loss due to insufficient coverage arises when a facility is located too far away from customer locations. The amount of demand lost is modeled as an increasing function of the travel distance. The second source of lost demand arises when the queue at a facility becomes too long. It is modeled as the proportion of balking customers in a Markovian queue with a fixed buffer length. The objective is to find the minimum number of facilities, and their locations, so that the amount of demand lost from either source does not exceed certain pre-set levels. After formulating the model, we derive and investigate several different integer programming formulations, focusing in particular on alternative representations of closest assignment constraints. We also investigate a wide variety of heuristic approaches, ranging from simple greedy-type heuristics, to heuristics based on time-limited branch and bound, tabu search, and random adaptive search heuristics. The results of an extensive set of computational experiments are presented and discussed.

Single facility location on a network under mill and delivered pricing

Firms normally use either a mill price or a delivered price policy, depending on market conditions (type of good, transportation way, customers location, costs, etc). In this paper, the problem of selecting the best location for an entering firm in competition with some pre-existing firms, under each price policy, is studied on a network for the first time. With mill pricing, an equilibrium in price rarely exists and it is assumed that all competing firms set a common mill price for all customers. With delivered pricing, there exists a Nash equilibrium in price and it is assumed that the equilibrium price in each area is offered to the customers in that area. In both cases, we consider that customers buy from the cheapest facility and the same rules are used for tie breaking in the lowest cost. While the profit maximization problem for the entering firm always has optimal solutions under mill pricing, this problem might not have an optimal solution under delivered pricing. We show some discretization results and give procedures to find the full set of optimal, or ε-optimal, solutions to the problem under the two price policies. A comparison of results with the two price policies is given by using an illustrative example.

Base Station Location and Service Assignments in W–CDMA Networks

Designing a wideband code division multiple access (W–CDMA) network is a complicated task requiring the selection of sites for radio towers, analysis of customer demand, and assurance of service quality in terms of signal-to-interference ratio requirements. This investigation presents a net-revenue maximization model that can help a network planner with the selection of tower sites and the calculation of service capacity. The integer programming model takes as input a set of candidate tower locations with corresponding costs, a number of customer locations with corresponding demand for traffic, and the revenue potential for each unit of capacity allocated to each demand point. Based on these data, the model can be used to determine the selection of radio towers and the service capacity of the resulting radio network. The basic model is a large integer program and requires a special algorithm for practical solution. Our algorithm uses a priority branching scheme, an optimization-gap tolerance between 1% and 10%, and two sets of global valid inequalities that tighten the upper bounds obtained from the linear programming relaxation. The algorithm has been implemented in software for the AMPL/CPLEX system and an empirical investigation has been conducted. Using over 300 problem instances with up to 40 towers and 250 service locations, various combinations of algorithm settings have been evaluated. Using the recommended setting results in a design tool that generally runs in under 20 minutes on a 667 MHz AlphaStation.

Approximate dynamic programming methods for an inventory allocation problem under uncertainty

AbstractWe propose two approximate dynamic programming methods to optimize the distribution operations of a company manufacturing a certain product at multiple production plants and shipping it to different customer locations for sale. We begin by formulating the problem as a dynamic program. Our first approximate dynamic programming method uses a linear approximation of the value function and computes the parameters of this approximation by using the linear programming representation of the dynamic program. Our second method relaxes the constraints that link the decisions for different production plants. Consequently, the dynamic program decomposes by the production plants. Computational experiments show that the proposed methods are computationally attractive, and in particular, the second method performs significantly better than standard benchmarks. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006

A genetic approach for freight transportation planning

PurposeThis purpose of this paper is to present a methodology for optimally planning long‐haul road transport activities through proper aggregation of customer orders in separate full‐truckload or less‐than‐truckload shipments in order to minimize total transportation costs.Design/methodology/approachThe model is applied to a specific Italian multi‐plant firm operating in the plastic film for packaging sector. The method, given the order quantities to be shipped and the location of customers, aggregates shipments in subgroups of compatible orders resorting to a heuristic procedure and successively consolidates them in optimized full truck load and less than truck load shipments resorting to a Genetic Algorithm in order to minimize total shipping costs respecting delivery due dates and proper geographical and truck capacity constraints.FindingsThe paper demonstrates that evolutionary computation techniques may be effective in tactical planning of transportation activities. The model shows that substantial savings on overall transportation cost may be achieved adopting the proposed methodology in a real life scenario.Research limitations/implicationsThe main limitation of this optimisation methodology is that an heuristic procedure is utilized instead of an enumerative approach in order to at first aggregate shipments in compatible sets before the optimisation algorithm carries out the assignments of customer orders to separate truckloads. Even if this implies that the solution could be sub‐optimal, it has demonstrated a very satisfactory performance and enables the problem to become manageable in real life settings.Practical implicationsThe proposed methodology enables to rapidly choose if a customer order should be shipped via a FTL or a LTL transport and performs the aggregation of different orders in separate shipments in order to minimize total transportation costs. As a consequence, the task of logistics managers is greatly simplified and consistently better performances respect manual planning can be obtained.Originality/valueThe described methodology is original in both the kind of approach adopted to solve the problem of optimising orders shipping in long‐haul direct shipping distribution logistics, and in the solution technique adopted which integrates heuristic algorithm and an original formulation of a GA optimisation problem. Moreover, the methodology solves both the truckload assignment problem and the choice of LTL vs FTL shipment thus representing an useful tool for logistics managers.

An optimization approach for planning daily drayage operations

Daily drayage operations involve moving loaded or empty equipment between customer locations and rail ramps. Our goal is to minimize the cost of daily drayage operations in a region on a given day. Drayage orders are generally pickup and delivery requests with time windows. The repositioning of empty equipment may also be required in order to facilitate loaded movements. The drayage orders are satisfied by a heterogeneous fleet of drivers. Driver routes must satisfy various operational constraints. We present an optimization methodology for finding cost-effective schedules for regional daily drayage operations. The core of the formulation is a set partitioning model whose columns represent routes. Routes are added to the formulation by column generation. We present numerical results for real-world data which demonstrate that our methodology produces low cost solutions in a reasonably short time.

Vehicle routing problem with simultaneous deliveries and pickups

The vehicle routing problem with backhauls involves the delivery and pickup of goods at different customer locations. In many practical situations, however, the same customer may require both a delivery of goods from the distribution centre and a pickup of recycled items simultaneously. In this paper, an insertion-based procedure to generate good initial solutions and a heuristic based on the record-to-record travel, tabu lists, and route improvement procedures are proposed to resolve the vehicle routing problems with simultaneous deliveries and pickups. Computational characteristics of the insertion-based procedure and the hybrid heuristic are evaluated through computational experiments. Computational results show that the insertion-based procedure obtained better solutions than those found in the literature. Computational experiments also show that the proposed hybrid heuristic is able to reduce the gap between initial solutions and optimal solutions effectively and is capable of obtaining optimal solutions very efficiently for small-sized problems.

Truck Route Planning in Nonstationary Stochastic Networks With Time Windows at Customer Locations

Most existing methods for truck route planning assume known static data in an environment that is time varying and uncertain by nature, which limits their widespread applicability. The development of intelligent transportation systems such as the use of information technologies reduces the level of uncertainties and makes the use of more appropriate dynamic formulations and solutions feasible. In this paper, a truck route planning problem called stochastic traveling salesman problem with time windows (STSPTW) in which traveling times along roads and service times at customer locations are stochastic processes is investigated. A methodology is developed to estimate the truck arrival time at each customer location. Using estimated arrival times, an approximate solution method based on dynamic programming is proposed. The algorithm finds the best route with minimum expected cost while it guarantees certain levels of service are met. Simulation results are used to demonstrate the efficiency of the proposed algorithm

The multiple disposal facilities and multiple inventory locations rollon–rolloff vehicle routing problem

In the Multiple disposal facilities and multiple inventory locations rollon–rolloff vehicle routing problem (M-RRVRP), one of the very important pickup and disposal problems in the sanitation industry, tractors move large trailers, one at a time, between customer locations such as construction sites and shopping centers, disposal facilities and inventory locations. In this paper, we model the M-RRVRP as a time constrained vehicle routing problem on a multigraph (TVRP-MG). We then formulate the TVRP-MG as a set partitioning problem with an additional constraint and describe an exact method for solving the TVRP-MG. This exact method is based on a bounding procedure that combines three lower bounds derived from different relaxations of the formulation of the problem. Further, we obtain a valid upper bound and show how this bounding procedure can transform the solution of a Lagrangean lower bound into a feasible solution. Our computational results show that the proposed method is very effective in deriving an optimal or near optimal solution to the M-RRVRP in a reasonable amount of computing time. Since the capacitated vehicle routing problem (CVRP) can be transformed into a TVRP-MG, we tested our procedure on 11 instances of the CVRP. Our computational results show that our procedure very effectively found the optimal solution to 7 of the 11 instances of the CVRP. In many cases, our procedure was at least 10 times faster than the procedure proposed by Fukasawa et al. Integer programming and combinatorial optimization, vol. 10. Lecture notes in computer science, vol. 3064. Berlin: Springer; 2004. p. 1–15. Both our procedure and the procedure of Fukasawa et al. Integer programming and combinatorial optimization, vol. 10. Lecture notes in computer science, vol. 3064. Berlin: Springer; 2004. p. 1–15 solved problem E-n76-k10, the most famous CVRP instance that until recently was unsolved.

Sysco Corp.

AbstractRetail ‐ Food & Beverage (MIC: 5.3 SIC: 5141 NAIC: 424410)Sysco is engaged in the marketing and distribution of food and related products to the foodservice or“food‐prepared‐away‐from‐home” industry. These services are performed for approximately 390,000 customers. Co.'s Broadline segment distributes a full line of food products and non‐food products to both traditional and chain restaurant customers. The SYGMA segment distributes a full line of food products and non‐food products to certain chain restaurant customer locations. The Other segment includes Co.'s specialty produce, custom‐cut meat, Asian cuisine foodservice and lodging industry products segments.

A scatter search-based heuristic to locate capacitated transshipment points

We consider a fixed charge two-stage location problem in which a given number of intermediate transshipment points are to be located between the supply plants and the customer locations. Both plants and transshipment points are capacitated. Scatter search is a population-based heuristic that has been applied to several combinatorial optimization problems. We develop an efficient scatter search-based heuristic approach with hybrid improvements including local search and path-relinking routines. Computational results demonstrate the effectiveness of the heuristic even for realistic problems with larger instances and tighter capacities.

APPROACHES FOR THE VEHICLE ROUTING PROBLEM WITH SIMULTANEOUS DELIVERIES AND PICKUPS

ABSTRACT The vehicle routing problem with backhauls deals with the delivery and pickup of goods at different customer locations. In many practical situations, however, the same customer may require both a delivery of goods from the central depot and a pickup of recycled/outdated items. In this paper, a parallel-insertion procedure is presented to obtain a quick solution for the vehicle routing problem with deliveries and pickups. A hybrid heuristic based on the simulated annealing method, tabu lists, and route improvement procedures is also proposed to improve the obtained solution. Computational characteristics of the proposed insertion-based procedure and the hybrid heuristic are evaluated through computational experiments. Computational experiments show that the parallel-insertion procedure obtains better solutions than those found in the open literature. Computational results also indicate that the proposed hybrid heuristic is able to reduce the gap between the obtained initial solution and optimal solution effectively and outperforms a metaheuristic tested in terms of solution quality, and is capable of obtaining optimal solutions very efficiently for small-scaled problems.

Sysco Corp.

Mergent's Dividend AchieversVolume 3, Issue 4 p. 271-271 U.S. Company Reports Sysco Corp.† First published: 10 October 2006 https://doi.org/10.1002/div.4914 † Contact: : Richard J. Schnieders — Chmn., Pres., C.E.O. Address: : 1390 Enclave Parkway, Houston, TX 77077-2099 Web Site: : www.sysco.com AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Retail - Food & Beverage (MIC: 5.3 SIC: 5141 NAIC: 424410) Sysco is engaged in the marketing and distribution of food and related products to the foodservice or “food-prepared-away-from-home” industry. These services are performed for approximately 390,000 customers. Co.'s Breadline segment distributes a full line of food products and non-food products to both traditional and chain restaurant customers. The SYGMA segment distributes a full line of food products and non-food products to certain chain restaurant customer locations. The Other segment includes Co.'s specialty produce, custom-cut meat, Asian cuisine foodservice and lodging industry products segments. Volume3, Issue4Autumn (Fall) 2006Pages 271-271 RelatedInformation

Sysco Corp.

Mergent's Dividend AchieversVolume 3, Issue 3 p. 272-272 U.S. Company Reports Sysco Corp.† First published: 30 June 2006 https://doi.org/10.1002/div.4498 † Contact: : Richard J. Schnieders — Chmn., Pres., C.E.O. Address: : 1390 Enclave Parkway, Houston, TX 77077-2099 Web Site: : www.sysco.com AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Retail - Food & Beverage (MIC: 5.3 SIC: 5141 NAIC: 424410) Sysco is engaged in the marketing and distribution of food and related products to the foodservice or “food-prepared-a way-from-home” industry. These services are performed for approximately 390,000 customers. Co.'s Broadline segment distributes a full line of food products and non-food products to both traditional and chain restaurant customers. The SYGMA segment distributes a full line of food products and non-food products to certain chain restaurant customer locations. The Other segment includes Co.'s specialty produce, custom-cut meat, Asian cuisine foodservice and lodging industry products segments. Volume3, Issue3Summer 2006Pages 272-272 RelatedInformation

Sysco Corp.

Mergent's Dividend AchieversVolume 3, Issue 2 p. 273-273 U.S. Company Reports Sysco Corp.† First published: 20 April 2006 https://doi.org/10.1002/div.4081 † Contact: : Richard I Schnieders — Chmn., Pres., C.E.O. Address: : 1390 Enclave Parkway, Houston, TX 77077-2099 Web Site: : www.sysco.com AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Abstract Retail - Food & Beverage (MIC: 5.3 SIC: 5141 NAIC: 424410) Sysco is engaged in the marketing and distribution of food and related products to the foodservice or “food-prepared-away-from-home” industry. These services are performed for approximately 390,000 customers. Co.'s Breadline segment distributes a full line of food products and non-food products to both traditional and chain restaurant customers. The SYGMA segment distributes a full line of food products and non-food products to certain chain restaurant customer locations. The Other segment includes Co.'s specialty produce, custom-cut meat, Asian cuisine foodservice and lodging industry products segments. Volume3, Issue2Spring 2006Pages 273-273 RelatedInformation

Metaheuristics applied to mixed and simultaneous extensions of vehicle routing problems with backhauls

Metaheuristics are a class of approximate methods designed to solve hard combinatorial optimization problems arising within various different areas. The importance of metaheuristics results from their ability to continue the search beyond a local optimum so that near-optimal or optimal solutions are efficiently found. In order to solve the backhauling problem associated with mixed and simultaneous delivery and pick-ups, this paper presents a hybrid algorithm which is comprised of the two metaheuristics of tabu search and variable neighbourhood descent. The primary challenge associated with backhauling consists of creating routes in which vehicles are not only required to deliver goods, but also to perform pick-ups at customer locations. The problems associated with these two categories of problems, however, have received little attention in the literature to date. A set of examples taken from the literature with Euclidean cost matrices are presented. Finally, some numerical results are illustrated to show the effectiveness of the proposed approach.

Decoupled substation reliability assessment

Distribution reliability studies usually involve a detailed model of the substation feeder and all of its sub-feeder elements. Load point indices are gathered at each of the customer locations and composite system wide indices are found based on all of the load point indices. In most of these reliability studies there is little detail given for the substation. Often times the substation is either represented by a transformer and a breaker or just a breaker. Typical substation outage events can contribute up to 20% of customer interruptions [Brown, RE. Electric power distribution reliability. New York: Marcel Dekker; 2002]. Therefore, it is important to have a detailed model of the substation included in distribution reliability studies to get accurate results. Including a detailed substation model in distribution reliability studies can greatly increase the size and complexity of the entire system model. One possible solution to this problem is to separate the substation reliability analysis from the distribution feeder reliability analysis. This would allow the use of specialized tools on the substation reliability analysis, while keeping the size and complexity down. It would also allow the use of existing software available for the distribution reliability analysis. In many companies the same substation arrangement is used multiple times throughout their system, so they would only need to model the substations once.

Sysco Corp.

AbstractRetail ‐ Food & Beverage (MIC: 5.3 SIC: 5141 NAIC: 424410)Sysco is engaged in the marketing and distribution of food and related products to the foodservice or “food‐prepared‐away‐from‐home” industry. These services are performed for approximately 400,000 customers from 150 distribution facilities located throughout U.S. and Canada. Co.'s Broadline segment distributes a full line of food products and non‐food products to both traditional and chain restaurant customers. The SYGMA segment distributes a full line of food products and non‐food products to certain chain restaurant customer locations. The Other segment includes Co.'s specialty produce, custom‐cut meat, Asian cuisine foodservice and lodging industry products segments.

Machine scheduling with deliveries to multiple customer locations

One important issue in production and logistics management is the coordination of activities between production and delivery. In this paper, we develop a single-machine scheduling model that incorporates routing decisions of a delivery vehicle which serves customers at different locations. The objective is to minimize the sum of job arrival times. The problem is NP-hard in the strong sense in general. We develop a polynomial time algorithm for the case when the number of customers is fixed. More efficient algorithms are developed for several special cases of the problem. In particular, an algorithm is developed for the single-customer case with a complexity lower than the existing ones.

AN ALGORITHM FOR THE GENERALIZED VEHICLE ROUTING PROBLEM WITH BACKHAULING

The Vehicle Routing Problem with Backhauling deals with the supply of finished goods from a depot to a number of delivery points, and picking up returnable items and bringing them back to the depot using a fleet of trucks. Traditionally, the objective of the problem has been to determine the truck routes such that the total number of trucks and/or the total distance traveled/total route cost are minimized. Most of the papers available in the literature in this connection deal with problems where the linehaul (having a demand for finished goods) and backhaul (having items to be returned to the depot) customers are different, and a customer may be visited by at most one truck limiting demand and returns at a location by the capacity of the truck. In this paper, we allow the linehaul and backhaul customers to be the same leading to simultaneous delivery and pickup at a customer location, and also there is no restriction on the quantity demanded at (to be returned from) a customer location. As such a customer may be visited by more than one truck and more than once by the same truck. We developed a Mixed Integer Linear programming (MILP) formulation of the problem and a route construction heuristic. The heuristic averaged 80 ms for 110 problems tested, and in 78 of them the heuristic costs were either equal to the optimal costs or at most equal to the upper bounds on the optimal costs obtained after running the optimization package for 30 min. Optimal solutions were obtained for 28 problems at an average time of 295 ms. The heuristic could match the optimal solutions for 22 of these problems at an average time of 71 ms.