Integer programming models for the pre-marshalling problem

[EN] The performance of shipping companies greatly depends on reduced berthing times. The trend towards bigger ships and shorter berthing times places severe stress on container terminals, which cannot simply increase the available cranes indefinitely. Therefore, the focus is on optimizing existing resources. An effective way of speeding up the loading/unloading operations of ships at the container terminal is to use the idle time before the arrival of a ship for sorting the stored containers in advance. The pre-marshalling problem consists in rearranging the containers placed in a bay in the order in which they will be required later, looking for a sequence with the minimum number of moves. With sorted bays, loading/unloading operations are significantly faster, as there is no longer a need to make unproductive moves in the bays once ships are berthed. In this paper, we address the pre-marshalling problem by developing and testing integer linear programming models. Two alternative families of models are proposed, as well as an iterative solution procedure that does not depend on a difficult to obtain upper bound. An extensive computational analysis has been carried out over several well-known datasets from the literature. This analysis has allowed us to test the performance of the models, and to conclude that the performance of the best proposed model is superior to that of previously published alternatives.This study has been partially supported by the Spanish Ministry of Education, Culture, and Sport, FPU Grant A-2015-12849 and by the Spanish Ministry of Economy and Competitiveness, under projects DPI2014-53665-P and DPI2015-65895-R, partially financed with FEDER funds.Parreño-Torres, C.; Alvarez-Valdes, R.; Ruiz García, R. (2019). Integer programming models for the pre-marshalling problem. European Journal of Operational Research. 274(1):142-154. https://doi.org/10.1016/j.ejor.2018.09.048S142154274

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Algorithms for Pallet Building and Truck Loading in an Interdepot Transportation Problem

This paper deals with the problem of a logistics company that has to serve its customers by first putting the products on pallets and then loading the pallets into trucks. Besides the standard geometric constraints of products not overlapping each other and not exceeding the dimensions of pallets and trucks, in this real problem, there are many other constraints, related to the total weight of the load, the maximum weight supported by each axle, and the distribution of the load inside the truck. Although the problem can be decomposed into two phases, pallet loading and truck loading, we have taken a combined approach, building and placing pallets at the same time. For each position in the truck, a pallet is built and tailored for that position according to the constraints of height and weight. We have developed a GRASP algorithm, in which the constructive algorithm is randomized and an improvement phase is added to obtain high-quality solutions. The algorithm has been tested on two sets of real instances with different characteristics, involving up to 44 trucks. The results show that solutions with an optimal or near optimal number of trucks are obtained in very short computing times

Minimizing weighted earliness-tardiness on a single machine with a common due date using quadratic models

In this paper we study the problem of minimizing weighted earliness and tardiness on a single machine when all the jobs share the same due date. We propose two quadratic integer programming models for solving both cases of unrestricted and restricted due dates, an auxiliary model based on unconstrained quadratic integer programming and an algorithmic scheme for solving each instance, according to its size and characteristics, in the most efficient way. The scheme is tested on a set of well-known test problems. By combining the solutions of the three models we prove the optimality of the solutions obtained for most of the problems. For large instances, although optimality cannot be proved, we actually obtain optimal solutions for all the tested instances.This study has been partially supported by the Spanish Ministry of Science and Technology, DPI2008-02700, cofinanced by FEDER funds, and by Project PCI08-0048-8577, Consejeria de Ciencia y Tecnologia, Junta de Comunidades de Castilla-La Mancha, and Generalitat Valenciana ACOMP/2009/264.Alvarez-Valdes Olaguibel, R.; Crespo, E.; Manuel Tamarit, J.; Villa Juliá, MF. (2012). Minimizing weighted earliness-tardiness on a single machine with a common due date using quadratic models. TOP. 20(3):754-767. https://doi.org/10.1007/s11750-010-0163-7S754767203Alidaee B, Kochenberger G, Ahmadian A (1994) 0–1 Quadratic programming approach for optimum solutions of two scheduling problems. Int J Syst Sci 25:401–408Baker KR, Scudder GD (1990) Sequencing with earliness and tardiness penalties: a review. Oper Res 38:22–36Billionnet A, Elloumi S (2007) Using a mixed integer quadratic programming solver for the unconstrained quadratic 0–1 problem. Math Program 109:55–68Billionnet A, Elloumi S, Plateau MC (2009) Improving the performance of standard solvers for quadratic 0–1 programs by a tight convex reformulation: the QCR method. Discrete Appl Math 157:1185–1197Biskup D, Feldman M (2001) Benchmarks for scheduling on a single machine against restrictive and unrestrictive common due dates. Comput Oper Res 28:787–801Cheng TCE, Kahlbacher HG (1991) A proof for the longest-job-first in one-machine scheduling. Nav Res Log 38:715–720De P, Gosh JB, Wells CE (1990) CON due-date determination and sequencing. Comput Oper Res 17:333–342Feldman M, Biskup D (2003) Single machine scheduling for minimizing earliness and tardiness penalties by meta-heuristic approaches. Comput Ind Eng 44:307–323Józefowska J (2007) Just-in-time scheduling. Springer, BerlinKanet JJ (1981) Minimizing the average deviation of job completion times about a common due date. Nav Res Log 28:643–651Kedad-Sidhoum S, Sourd F (2010) Fast neighborhood search for the single machine earliness–tardiness problem. Comput Oper Res 37:1464–1471Hall NG, Posner ME (1991) Earliness–tardiness scheduling problem, I: Weighted deviation of completion times about a common due date. Oper Res 39:836–846Hall NG, Kubiak W, Sethi SP (1991) Earliness–tardiness scheduling problem, II: Deviation of completion times about a restrictive common due date. Oper Res 39:847–856Hino CM, Ronconi DP, Mendes AB (2005) Minimizing earliness and tardiness penalties in a single-machine problem with a common due date. Eur J Oper Res 55:190–201Hoogeveen JA, van de Velde SL (1991) Scheduling around a small common due date. Eur J Oper Res 55:237–242Liao CJ, Cheng CC (2007) A variable neighbourhood search for minimizing single machine weighted earliness and tardiness with common due date. Comput Ind Eng 52:404–413Lin S-W, Chou S-Y, Ying K-C (2007) A sequential exchange approach for minimizing earliness–tardiness penalties of single-machine scheduling with a common due date. Eur J Oper Res 177:1294–1301Nearchou AC (2008) A differential evolution approach for the common due date early/tardy job scheduling problem. Comput Oper Res 35:1329–1343Oral M, Kettani O (1987) Equivalent formulations of nonlinear integer problems for efficient optimization. Manag Sci 36:115–119Panwalkar SS, Smith ML, Seidman A (1982) Common due date assignment to minimize total penalty for the one machine scheduling problem. Oper Res 30:391–399Plateau MC, Rios-Solis Y (2010) Optimal solutions for unrelated parallel machines scheduling problems using convex quadratic reformulations. Eur J Oper Res 201:729–736Skutella M (2001) Convex quadratic and semidefinite programming relaxations in scheduling. J ACM 48:206–242Sourd F (2009) New exact algorithms for on-machine earliness–tardiness scheduling. INFORMS J Comput 21:167–175Sourd F, Kedad-Sidhoum S (2003) The one machine problem with earliness and tardiness penalties. J Sched 6:533–549Sourd F, Kedad-Sidhoum S (2008) A faster branch-and-bound algorithm for the earliness–tardiness scheduling problem. J Sched 11:49–58Tanaka S, Fujikuma S, Araki M (2009) An exact algorithm for single-machine scheduling without machine idle time. J Sched 12:575–593Webster ST (1997) The complexity of scheduling job families about a common due date. Oper Res Lett 20:65–7

The berth allocation problem in terminals with irregular layouts

As international trade thrives, terminals attempt to obtain higher revenue while coping with an increased complexity with regard to terminal management operations. One of the most prevalent problems such terminals face is the Berth Allocation Problem (BAP), which concerns allocating vessels to a set of berths and time slots while simultaneously minimizing objectives such as total stay time or total assignment cost. Complex layouts of real terminals introduce spatial constraints which limit the mooring and departure of vessels. Although significant research has been conducted regarding the BAP, these real-world restrictions have not been taken into account in a general way. The present work proposes both a mixed integer linear programming formulation and a heuristic, which are capable of obtaining optimal or near-optimal solutions to this novel variant of the BAP. In order to assess the quality of the heuristic, which is being employed in a real tank terminal in Belgium, it is compared against the exact approach by way of randomly-generated instances and real-world benchmark sets derived from the tank terminal.status: publishe